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  • Articles  (66)
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  • Articles  (66)
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  • Springer  (66)
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  • 1
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    Computing 33 (1984), S. 247-257 
    ISSN: 1436-5057
    Keywords: Random variate generation ; simulation ; log concavity ; inequalities
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Description / Table of Contents: Zusammenfassung Wir legen einen kurzen Algorithmus zur Erzeugung von Zufallsveränderlichen mit log-konkaver Dichtef aufR mit bekanntem Median-Wert vor. Die mittlere Anzahl der erforderlichen Operationen ist unabhängig vonf. Die log-konkaven Dichtefunktionen beschreiben u. a. die Normal-, Gamma-, Weibull-, Beta-, Potenzexponential- (alle mit Formparameter mindestens 1), Perks- und Extremwert-Verteilung.
    Notes: Abstract We present a short algorithm for generating random variates with log-concave densityf onR and known mode in average number of operations independent off. Included in this class are the normal, gamma, Weibull, beta and exponential power (all with shape parameters at least 1), logistic, hyperbolic secant and extreme value distributions. The algorithm merely requires the presence of a uniform [0, 1] random number generator and a subprogram for computingf. It can be implemented in about 10 lines of FORTRAN code.
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  • 2
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    Formal methods in system design 6 (1995), S. 11-44 
    ISSN: 1572-8102
    Keywords: abstract interpretation ; simulation ; property preservation ; model-checking
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract We study property preserving transformations for reactive systems. The main idea is the use of simulations parameterized by Galois connections (α, γ), relating the lattices of properties of two systems. We propose and study a notion of preservation of properties expressed by formulas of a logic, by a function α mapping sets of states of a systemS into sets of states of a systemS'. We give results on the preservation of properties expressed in sublanguages of the branching time μ-calculus when two systemsS andS' are related via (α, γ)-simulations. They can be used to verify a property for a system by verifying the same property on a simpler system which is an abstraction of it. We show also under which conditions abstraction of concurrent systems can be computed from the abstraction of their components. This allows a compositional application of the proposed verification method. This is a revised version of the papers [2] and [16]; the results are fully developed in [28].
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  • 3
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    Queueing systems 19 (1995), S. 169-192 
    ISSN: 1572-9443
    Keywords: Continuity ; rates of convergence ; robust estimation ; queueing systems ; simulation ; regenerative processes
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Leta ands denote the inter arrival times and service times in aGI/GI/1 queue. Let a(n), s(n) be the r.v.s. with distributions as the estimated distributions ofa ands from iid samples ofa ands of sizesn. Letw be a r.v. with the stationary distribution π of the waiting times of the queue with input(a,s). We consider the problem of estimatingE[w α], α〉 0 and α via simulations when (a (n),s(n)) are used as input. Conditions for the accuracy of the asymptotic estimate, continuity of the asymptotic variance and uniformity in the rate of convergence to the estimate are obtained. We also obtain rates of convergence for sample moments, the empirical process and the quantile process for the regenerative processes. Robust estimates are also obtained when an outlier contaminated sample ofa ands is provided. In the process we obtain consistency, continuity and asymptotic normality of M-estimators for stationary sequences. Some robustness results for Markov processes are included.
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  • 4
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    Queueing systems 21 (1995), S. 391-413 
    ISSN: 1572-9443
    Keywords: Dynamic scheduling control ; queueing network ; fluid network ; queueing theory ; flow control ; simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Motivated by dynamic scheduling control for queueing networks, Chen and Yao [8] developed a systematic method to generate dynamic scheduling control policies for a fluid network, a simple and highly aggregated model that approximates the queueing network. This study addresses the question of how good these fluid policies are as heuristic scheduling policies for queueing networks. Using simulation on some examples these heuristic policies are compared with traditional simple scheduling rules. The results show that the heuristic policies perform at least comparably to classical priority rules, regardless of the assumptions made about the traffic intensities and the arrival and service time distributions. However, they are certainly not always the best and, even when they are, the improvement is seldom dramatic. The comparative advantage of these policies may lie in their application to nonstationary situations such as might occur with unreliable machines or nonstationary demand patterns.
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  • 5
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    Queueing systems 27 (1997), S. 37-54 
    ISSN: 1572-9443
    Keywords: massive parallel processing ; simulation ; MIMD and SIMD parallel computers ; scalable algorithm ; G/G/1 queue ; longest path ; queueing networks
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This paper presents several basic algorithms for the parallel simulation of G/G/1 queueing systems and certain networks of such systems. The coverage includes systems subject to manufacturing or communication blocking, or to loss of customer due to capacity constraints. The key idea is that the customer departure times are represented by longest-path distance in directed graphs instead of by the usual recursive equations. This representation leads to scalable algorithms with a high degree of parallelism that can be implemented on either MIMD or SIMD parallel computers.
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  • 6
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    Queueing systems 31 (1999), S. 43-58 
    ISSN: 1572-9443
    Keywords: perturbation analysis ; sample path analysis ; queueing theory ; simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract We study infinitesimal perturbation analysis (IPA) for queueing networks with general service time distributions. By “general” we mean that the distributions may have discrete components. We show that in the presence of service time distributions with discrete components commuting condition (CC) is no longer sufficient for unbiasedness of IPA. To overcome this difficulty, we introduce the notion of separability of real‐valued random variables, and show that separability of service times together with (CC) establishes unbiasedness of IPA for queueing systems with general service time distributions. It turns out that the piecewise analyticity of service times is a sufficient condition for separability.
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  • 7
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    Queueing systems 19 (1995), S. 247-268 
    ISSN: 1572-9443
    Keywords: Sensitivity coefficient ; score function ; driving sequence ; queuing model ; simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Queuing models described as regenerative processes driven by several sequences are under investigation. Occurrence times in these sequences are supposed to be asynchronous, in general. Sensitivity coefficients that are derivatives of some stationary performance measures with respect to definite parameters as well as derivatives of higher orders are derived for such queuing models. These sensitivity coefficients can be evaluated by simulation.
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  • 8
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    Computing 30 (1983), S. 185-188 
    ISSN: 1436-5057
    Keywords: 62E30 ; 62E25 ; Random numbers ; simulation ; gamma distribution ; pseudo-random
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Description / Table of Contents: Zusammenfassung Es wird eine Modifikation des Algorithmus von Ahrens und Dieter [1] angegeben, welcher gammaverteilte Zufallsvariable mit einem Formparameter kleiner Eins erzeugt. Der modifizierte Algorithmus ist deutlich schneller, obwohl er kaum komplexer ist als der ursprüngliche.
    Notes: Abstract A modification is given for an algorithm of Ahrens and Dieter [1] which generates random Gamma variates with shape parameter less than unity. The modified algorithm is substantially faster, although hardly more complex than the original one.
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  • 9
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    Journal of intelligent and robotic systems 23 (1998), S. 379-405 
    ISSN: 1573-0409
    Keywords: flexible drive system ; fuzzy-enhanced adaptive control ; genetic algorithms ; friction control
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract When a mechatronic system is in slow speed motion, serious effect of nonlinear friction plays a key role in its control design. In this paper, a stable adaptive control for drive systems including transmission flexibility and friction, based on the Lyapunov stability theory, is first proposed. For ease of design, the friction is fictitiously assumed as an unknown disturbance in the derivation of the adaptive control law. Genetic algorithms are then suggested for learning the structure and parameters of the fuzzy-enhancing strategy for the adaptive control to improve system's transient performance and robustness with respect to uncertainty. The integrated fuzzy-enhanced adaptive control is well tested via computer simulations using the new complete dynamic friction model recently suggested by Canudas de Wit et al. for modeling the real friction phenomena. Much lower critical velocity of a flexible drive system that determines system's low-speed performance bound can be obtained using the proposed hybrid control strategy.
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  • 10
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    Higher-order and symbolic computation 10 (1998), S. 237-271 
    ISSN: 1573-0557
    Keywords: abstract interpretation ; operational semantics ; collecting semantics ; simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract We present trace-based abstract interpretation, a unification of severallines of research on applying Cousot-Cousot-style abstract interpretation a.i. tooperational semantics definitions (such as flowchart, big-step, and small-step semantics)that express a program‘s semantics as a concrete computation tree of trace paths. Aprogram‘s trace-based a.i. is also a computation tree whose nodes contain abstractions ofstate and whose paths simulate the paths in the program‘s concrete computation tree.Using such computation trees, we provide a simple explanation of the central concept of collecting semantics, and we distinguish concrete from abstract collectingsemantics and state-based from path-based collecting semantics. We also expose therelationship between collecting semantics extraction and results garnered from flow-analytic and model-checking-based analysis techniques. We adapt concepts fromconcurrency theory to formalize “safe” and “live” a.i.‘s for computation trees; in particular, coinduction techniques help extend fundamental results to infinite computation trees. Problems specific to the various operational semantics methodologies are discussed: Big-step semantics cannot express divergence, so we employ a mixture of induction andcoinduction in response; small-step semantics generate sequences of programconfigurations unbounded in size, so we abstractly interpret source language syntax.Applications of trace-based a.i. to data-flow analysis, model checking, closure analysis,and concurrency theory are demonstrated.
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  • 11
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    The journal of supercomputing 11 (1997), S. 255-278 
    ISSN: 1573-0484
    Keywords: Ewald ; parallel ; T3E ; simulation ; electrostatic ; molecular dynamics ; PME
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract We report our work to parallelize the Particle Mesh Ewald (PME) method to compute the long-range electrostatic interactions in the molecular dynamics program AMBER and to extend the scalability of the PME method to hundreds of processors.
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  • 12
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    Journal of intelligent and robotic systems 23 (1998), S. 331-349 
    ISSN: 1573-0409
    Keywords: constrained robots ; genetic algorithms ; learning ; friction compensation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract In this paper, the issues of contact friction compensation for constrained robots are presented. The proposed design consists of two loops. The inner loop is for the inverse dynamics control which linearizes the system by canceling nonlinear dynamics, while the outer loop is for friction compensation. Although various models of friction have been proposed in many engineering applications, frictional force can be modeled by the Coulomb friction plus the viscous force. Based on such a model, an on-line genetic algorithm is proposed to learn the friction coefficients for friction model. The friction compensation control input is also implemented in terms of the friction coefficients to cancel the effect of unknown friction. By the guidance of the fitness function, the genetic learning algorithm searches for the best-fit value in a way like the natural surviving laws. Simulation results demonstrate that the proposed on-line genetic algorithm can achieve good friction compensation even under the conditions of measurement noise and system uncertainty. Moreover, the proposed control scheme is also found to be feasible for friction compensation of friction model with Stribeck effect and position-dependent friction model.
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  • 13
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    Journal of intelligent and robotic systems 23 (1998), S. 351-377 
    ISSN: 1573-0409
    Keywords: robots ; trajectory generation ; raster scanning ; genetic algorithms ; redundancy ; obstacle avoidance
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract An algorithm for Cartesian trajectory generation by redundant robots in environments with obstacles is presented. The algorithm combines a raster scanning technique, genetic algorithms and functions for interpolation in the joint coordinates space in order to approximate a desired Cartesian curve by the robot's hand tip under maximum allowed position deviation. A raster scanning technique determines a minimal set of knot points on the desired curve in order to generate a Cartesian trajectory with bounded position approximation error. Genetic algorithms are used to determine an acceptable robot configuration under obstacle avoidance constraints corresponding to a knot point. Robot motion between two successive knot points is finally achieved using well known interpolation techniques in the joint coordinates space. The proposed algorithm is analyzed and its performance is demonstrated through simulated experiments carried out on planar redundant robots.
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  • 14
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    Journal of intelligent and robotic systems 17 (1996), S. 309-325 
    ISSN: 1573-0409
    Keywords: modeling ; camera ; CCD ; subpixel ; simulation ; vision ; image ; diffusion ; CAD ; CIM ; bias
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract In this paper we propose a modeling of an acquisition line made up of a CCD camera, a lens and a frame grabber card. The purpose of this modeling is to simulate the acquisition process in order to obtain images of virtual objects. The response time has to be short enough to permit interactive simulation. All the stages are modelised: in the first phase, we present a geometric model which supplies a point to point transformation that provides, for a space point in the camera field, the corresponding point on the plane of the CCD sensor. The second phase consists of modeling the discrete space which implies passing from the continous known object view to a discrete image, in accordance with the different orgin of the contrast loss. In the third phase, the video signal is reconstituted in order to be sampled by the frame grabber card. The practical results are close to reality when compared to image processing. This tool makes it possible to obtain a short computation time simulation of a vision sensor. This enables interactivity either with the user or with software for the design/simulation of an industrial workshop equipped with a vision system. It makes testing possible and validates the choice of sensor placement and image processing and analysis. Thanks to this simulation tool, we can control perfectly the position of the object image placed under the camera and in this way, we can characterise the performance of subpixel accuracy determining methods for object positioning.
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  • 15
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    Journal of intelligent and robotic systems 24 (1999), S. 125-149 
    ISSN: 1573-0409
    Keywords: planning ; control ; multi-fingered robot hand ; optimization ; internal force ; simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract In this paper, the problem of controlling multi-fingered robot hands with rolling and sliding contacts is addressed. Several issues are explored. These issues involve the kinematic analysis and modeling, the dynamic analysis and control, and the coordination of a multi-fingered robot hand system. Based on a hand-object system in which the contacts are allowed to both roll and slide, a kinematic model is derived and analyzed. Also, the dynamic model of the hand-object system with relative motion contacts is studied. A control law is proposed to guarantee the asymptotic tracking of the object trajectory together with the desired rolling and/or sliding motions along the surface of the object. A planning approach is then introduced to minimize the contact forces so that the desired motion of the object and the relative motions between the fingers and the object can be achieved. Simulation results which support the theoretical development are presented.
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  • 16
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    Journal of intelligent and robotic systems 18 (1997), S. 209-248 
    ISSN: 1573-0409
    Keywords: acrobot ; robotics ; fuzzy control ; genetic algorithms
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract The acrobot is an underactuated two-link planar robot that mimics the human acrobat who hangs from a bar and tries to swing up to a perfectly balanced upside-down position with his/her hands still on the bar. In this paper we develop intelligent controllers for swing-up and balancing of the acrobot. In particular, we first develop classical, fuzzy, and adaptive fuzzy controllers to balance the acrobot in its inverted unstable equilibrium region. Next, a proportional-derivative (PD) controller with inner-loop partial feedback linearization, a state-feedback, and a fuzzy controller are developed to swing up the acrobot from its stable equilibrium position to the inverted region, where we use a balancing controller to ‘catch’ and balance it. At the same time, we develop two genetic algorithms for tuning the balancing and swing-up controllers, and show how these can be used to help optimize the performance of the controllers. Overall, this paper provides (i) a case study of the development of a variety of intelligent controllers for a challenging application, (ii) a comparative analysis of intelligent vs. conventional control methods (including the linear quadratic regulator and feedback linearization) for this application, and (iii) a case study of the development of genetic algorithms for off-line computer-aided-design of both conventional and intelligent control systems.
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  • 17
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    Journal of intelligent and robotic systems 20 (1997), S. 251-273 
    ISSN: 1573-0409
    Keywords: robot control ; adaptive behavior ; robust intelligent control ; multi-robot systems ; machine learning ; neural networks ; genetic algorithms ; cognitive architecture.
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract The objective of this paper is to present a cognitive architecture thatutilizes three different methodologies for adaptive, robust control ofrobots behaving intelligently in a team. The robots interact within a worldof objects, and obstacles, performing tasks robustly, while improving theirperformance through learning. The adaptive control of the robots has beenachieved by a novel control system. The Tropism-based cognitive architecturefor the individual behavior of robots in a colony is demonstrated throughexperimental investigation of the robot colony. This architecture is basedon representation of the likes and dislikes of the robots. It is shown thatthe novel architecture is not only robust, but also provides the robots withintelligent adaptive behavior. This objective is achieved by utilization ofthree different techniques of neural networks, machine learning, and geneticalgorithms. Each of these methodologies are applied to the tropismarchitecture, resulting in improvements in the task performance of the robotteam, demonstrating the adaptability and robustness of the proposed controlsystem.
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  • 18
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    Journal of intelligent and robotic systems 25 (1999), S. 255-275 
    ISSN: 1573-0409
    Keywords: hierarchical fuzzy control ; genetic algorithms ; flexible C-axis ; dynamic friction ; low-speed control
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract A combined PD and hierarchical fuzzy control is proposed for the low-speed control of the C-axis of CNC turning centers considering the effects of transmission flexibility and complex nonlinear friction. Learning of the hierarchical structure and parameters of the suggested control strategy is carried out by using the genetic algorithms. The proposed algorithm consists of two phases: the first one is to search the best hierarchy, and the second to tune the consequent center values of the constituent fuzzy logic systems into the hierarchy. For the least total control rule number, the hierarchical fuzzy controller is chosen to include only the simple two-input/one-output fuzzy systems, and both binary and decimal genes are used for the selection, crossover and mutation of the genetic algorithm. The proposed approach is validated by the computer simulation. Each generation consists of 30 individuals: ten reproduced from its parent generation, ten generated by crossover, and the other ten by mutation. In the simulations, the C-axis is assumed to be driven by a vector-controlled AC induction motor, and the dynamic friction model suggested by Canudas de Wit et al. in 1995 is used.
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    Machine learning 21 (1995), S. 11-33 
    ISSN: 0885-6125
    Keywords: genetic algorithms ; DNA fragment assembly ; human genome project ; ordering problems ; edge-recombination crossover ; building blocks
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract We study different genetic algorithm operators for one permutation problem associated with the Human Genome Project—the assembly of DNA sequence fragments from a parent clone whose sequence is unknown into a consensus sequence corresponding to the parent sequence. The sorted-order representation, which does not require specialized operators, is compared with a more traditional permutation representation, which does require specialized operators. The two representations and their associated operators are compared on problems ranging from 2K to 34K base pairs (KB). Edge-recombination crossover used in conjunction with several specialized operators is found to perform best in these experiments; these operators solved a 10KB sequence, consisting of 177 fragments, with no manual intervention. Natural building blocks in the problem are exploited at progressively higher levels through “macro-operators.” This significantly improves performance.
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    Machine learning 21 (1995), S. 11-33 
    ISSN: 0885-6125
    Keywords: genetic algorithms ; DNA fragment assembly ; human genome project ; ordering problems ; edgerecombination crossover ; building blocks
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract We study different genetic algorithm operators for one permutation problem associated with the Human Genome Project—the assembly of DNA sequence fragments from a parent clone whose sequence is unknown into a consensus sequence corresponding to the parent sequence. The sorted-order representation, which does not require specialized operators, is compared with a more traditional permutation representation, which does require specialized operators. The two representations and their associated operators are compared on problems ranging from 2K to 34K base pairs (KB). Edge-recombination crossover used in conjunction with several specialized operators is found to perform best in these experiments; these operators solved a 10KB sequence, consisting of 177 fragments, with no manual intervention. Natural building blocks in the problem are exploited at progressively higher levels through “macro-operators.” This significantly improves performance.
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    Machine learning 19 (1995), S. 209-240 
    ISSN: 0885-6125
    Keywords: learning classifier systems ; reinforcement learning ; genetic algorithms ; animat problem
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract In this article we investigate the feasibility of using learning classifier systems as a tool for building adaptive control systems for real robots. Their use on real robots imposes efficiency constraints which are addressed by three main tools: parallelism, distributed architecture, and training. Parallelism is useful to speed up computation and to increase the flexibility of the learning system design. Distributed architecture helps in making it possible to decompose the overall task into a set of simpler learning tasks. Finally, training provides guidance to the system while learning, shortening the number of cycles required to learn. These tools and the issues they raise are first studied in simulation, and then the experience gained with simulations is used to implement the learning system on the real robot. Results have shown that with this approach it is possible to let the AutonoMouse, a small real robot, learn to approach a light source under a number of different noise and lesion conditions.
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    Machine learning 19 (1995), S. 209-240 
    ISSN: 0885-6125
    Keywords: learning classifier systems ; reinforcement learning ; genetic algorithms ; animat problem
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    Topics: Computer Science
    Notes: Abstract In this article we investigate the feasibility of using learning classifier systems as a tool for building adaptive control systems for real robots. Their use on real robots imposes efficiency constraints which are addressed by three main tools: parallelism, distributed architecture, and training. Parallelism is useful to speed up computation and to increase the flexibility of the learning system design. Distributed architecture helps in making it possible to decompose the overall task into a set of simpler learning tasks. Finally, training provides guidance to the system while learning, shortening the number of cycles required to learn. These tools and the issues they raise are first studied in simulation, and then the experience gained with simulations is used to implement the learning system on the real robot. Results have shown that with this approach it is possible to let the AutonoMouse, a small real robot, learn to approach a light source under a number of different noise and lesion conditions.
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    Soft computing 2 (1998), S. 61-72 
    ISSN: 1433-7479
    Keywords: Keywords fuzzy sets ; genetic algorithms ; information granularity ; weak encoding ; fuzzy metarules
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract  This paper elaborates on a new paradigm of computing embracing fuzzy sets and evolutionary methods (specially genetic algorithms). We discuss conceptual and algorithmic enhancements to the individual methods. Fuzzy sets are geared toward granular information processing. Evolutionary computing are population-based optimization methods. In this way, as being components of any hybrid structure, they naturally complement each other. The study reveals a number of representative symbiotic links between fuzzy and genetic computing and provides with relevant illustrative examples.
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    Artificial life and robotics 1 (1997), S. 35-38 
    ISSN: 1614-7456
    Keywords: artificial evolution ; genetic algorithms ; evolutionary robotics
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    Topics: Computer Science
    Notes: Abstract Artificial evolution as a design methodology allows the relaxation of many of the constraints that have held back conventional methods. It does not require a complete prior analysis and decomposition of the task to be tackled, as human designers require. However, this freedom comes at some cost; there are a whole new set of issues relating to evolution that must be considered. Standard genetic algorithms may not be appropriate for incremental evolution of robot controllers. Species adaptation genetic algorithms, (SAGA) have been developed to meet these special needs. The main cost of an evolutionary approach is the large number of trials that are required. Simulations-especially those involving vision in complex environments, or modeling detailed semiconductor physics—may not be adequate or practical. Examples of evolved robots will be discussed, including a specialized piece of equipment which allows a robot to be tested using simple vision in real time, and what is believed to be the first successful example of an evolved hardware controller for a robot.
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    Computational economics 13 (1999), S. 93-101 
    ISSN: 1572-9974
    Keywords: efficiency ; multivariate probit ; quasi maximum likelihood ; simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Economics
    Notes: Abstract This paper discusses the most efficient estimator among Quasi Maximum Likelihood Estimators using at most two levels of numerical integration, for the multivariate probit model. Simulations show that this estimator is more efficient but not more costly than the second-best alternative. However, its added efficiency depends on the correlation structure.
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    Computational economics 13 (1999), S. 41-60 
    ISSN: 1572-9974
    Keywords: genetic algorithms ; learning ; equilibrium selection ; heterogeneous beliefs
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Economics
    Notes: Abstract We study a general equilibrium system where agents have heterogeneous beliefs concerning realizations of possible outcomes. The actual outcomes feed back into beliefs thus creating a complicated nonlinear system. Beliefs are updated via a genetic algorithm learning process which we interpret as representing communication among agents in the economy. We are able to illustrate a simple principle: genetic algorithms can be implemented so that they represent pure learning effects (i.e., beliefs updating based on realizations of endogenous variables in an environment with heterogeneous beliefs). Agents optimally solve their maximization problem at each date given their beliefs at each date. We report the results of a set of computational experiments in which we find that our population of artificial adaptive agents is usually able to coordinate their beliefs so as to achieve the Pareto superior rational expectations equilibrium of the model.
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    Computational economics 9 (1996), S. 275-298 
    ISSN: 1572-9974
    Keywords: genetic programming ; genetic algorithms ; evolutionary search ; optimal growth ; econometrics ; nonparametric regression
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Economics
    Notes: Abstract This paper discusses economic applications of a recently developed artificial intelligence technique-Koza's genetic programming (GP). GP is an evolutionary search method related to genetic algorithms. In GP, populations of potential solutions consist of executable computer algorithms, rather than coded strings. The paper provides an overview of how GP works, and illustrates with two applications: solving for the policy function in a simple optimal growth model, and estimating an unusual regression function. Results suggest that the GP search method can be an interesting and effective tool for economists.
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    Computational economics 10 (1997), S. 107-118 
    ISSN: 1572-9974
    Keywords: visualisation ; simulation ; linear quadratic control ; observer ; Kalmanfilter
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Economics
    Notes: Abstract Simulation of economic models is frequently used in the investigation of economic policy. Yet one of the problems with simulation is that it can be difficult to appreciate the model properties due to the nature of the simulation process. Stochastic simulation, for example, can produce large quantities of output which can be difficult to comprehend. Further, when mathematically sophisticated techniques such as the use of optimal control and Kalman Filtering are applied to models, the simulation process can become even more complex. Visualisation techniques in model building, simulation, and analysis of simulation output can help reduce the complexity. This is especially the case with interactive simulation. In this paper we investigate the use of visualisation in simulation by examining the application of optimal control techniques to a stochastic forward looking analytic economic model. We also use interactive object oriented simulation software where objects, such as components of models or graphs of outputs, can be visually manipulated to form simulation systems. We find that the use of visualisation can make the investigation of policy analysis issues with such models more comprehensible.
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    Applied intelligence 11 (1999), S. 277-284 
    ISSN: 1573-7497
    Keywords: genetic algorithms ; classification ; data mining
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    Topics: Computer Science
    Notes: Abstract A common approach to evaluating competing models in a classification context is via accuracy on a test set or on cross-validation sets. However, this can be computationally costly when using genetic algorithms with large datasets and the benefits of performing a wide search are compromised by the fact that estimates of the generalization abilities of competing models are subject to noise. This paper shows that clear advantages can be gained by using samples of the test set when evaluating competing models. Further, that applying statistical tests in combination with Occam's razor produces parsimonious models, matches the level of evaluation to the state of the search and retains the speed advantages of test set sampling.
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    Journal of network and systems management 3 (1995), S. 371-380 
    ISSN: 1573-7705
    Keywords: Telephone traffic ; network management ; control theory ; dynamic flows ; stability ; routing algorithms ; broadband networks ; simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract The control of telephony traffic is the task of network management and routing algorithms. In this paper, a study of two trunk groups carrying telephony traffic is used to show that instabilities can arise if there is a delay in getting feedback information for a network controller. The network controller seeks to balance the traffic in the two trunk groups, which may represent two paths from a source to a destination. An analysis shows how factors such as holding time, controller gain and feedback delay influence stability. Simulation of a two service case is also carried out to show that the same instabilities can arise.
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    Neural processing letters 10 (1999), S. 223-229 
    ISSN: 1573-773X
    Keywords: artificial neural networks ; genetic algorithms ; evolutionary networks ; adaptive image processing
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    Topics: Computer Science
    Notes: Abstract We describe an efficient method of combining the global search of genetic algorithms (GAs) with the local search of gradient descent algorithms. Each technique optimizes a mutually exclusive subset of the network's weight parameters. The GA chromosome fixes the feature detectors and their location, and a gradient descent algorithm starting from random initial values optimizes the remaining weights. Three algorithms having different methods of encoding hidden unit weights in the chromosome are applied to multilayer perceptrons (MLPs) which classify noisy digital images. The fitness function measures the MLP classification accuracy together with the confidence of the networks.
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    Neural processing letters 4 (1996), S. 149-155 
    ISSN: 1573-773X
    Keywords: adaptation ; diploidy ; genetic algorithms ; genotype-phenotype mapping ; neural networks
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    Topics: Computer Science
    Notes: Abstract In nature the genotype of many organisms exhibits diploidy, i.e., it includes two copies of every gene. In this paper we describe the results of simulations comparing the behavior of haploid and diploid populations of ecological neural networks living in both fixed and changing environments. We show that diploid genotypes create more variability in fitness in the population than haploid genotypes and buffer better environmental change; as a consequence, if one wants to obtain good results for both average and peak fitness in a single population one should choose a diploid population with an appropriate mutation rate. Some results of our simulations parallel biological findings.
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    Applied intelligence 6 (1996), S. 241-252 
    ISSN: 1573-7497
    Keywords: vehicle routing ; time windows ; neural networks ; genetic algorithms
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    Topics: Computer Science
    Notes: Abstract A competitive neural network model and a genetic algorithm are used to improve the initialization and construction phase of a parallel insertion heuristic for the vehicle routing problem with time windows. The neural network identifies seed customers that are distributed over the entire geographic area during the initialization phase, while the genetic algorithm finds good parameter settings in the route construction phase that follows. Computational results on a standard set of problems are also reported.
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    Applied intelligence 6 (1996), S. 345-355 
    ISSN: 1573-7497
    Keywords: vehicle routing ; backhauling ; time windows ; genetic algorithms ; heuristics
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    Topics: Computer Science
    Notes: Abstract In this paper, a greedy route construction heuristic for a vehicle routing problem with backhauling is described. This heuristic inserts customers one by one into the routes using a fixed a priori ordering of customers. Then, a genetic algorithm is used to identify an ordering that produces good routes. Numerical comparisons are provided with an exact algorithm and with other heuristic approaches.
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    Applied intelligence 8 (1998), S. 195-218 
    ISSN: 1573-7497
    Keywords: modelling ; simulation ; teams ; coordination ; organizations
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    Topics: Computer Science
    Notes: Abstract The problem of modelling air missions is part of a larger problem—simulating possible war-like scenarios in the air, sea, and on land. In modelling such military systems one is required to model the behaviour of various actors and the resources that are available to them. One aspect of this problem is the modelling of a group of actors as a team and then modelling the coordinated behaviour of such a team to achieve a joint goal. In the domain of air mission modelling the actors are pilots who control aircraft and their behaviour is referred to as tactics. In this paper we present the approach we adopted in modelling teams and team tactics as part of the development of the Smart Whole AiR Mission Model (SWARMM) for the Air Operations Division of the Australian Defence Science and Technology Organization. In our approach teams are composed of sub-teams and adopt organizational structures. Such structures define the responsibilities of the sub-teams towards the mission to be achieved as well as towards the control and coordination of the sub-teams. We also describe how communication is used when adopting a variety of control and coordination strategies and how one could reason about the choice of organizational structures for a given mission and situation.
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    Autonomous robots 3 (1996), S. 253-268 
    ISSN: 1573-7527
    Keywords: underwater robotics ; hydrodynamics ; simulation ; articulated mechanisms ; tree topologies ; object-oriented design
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract This paper presents a computational framework for efficiently simulating the dynamics and hydrodynamics of Underwater Robotic Vehicle (URV) systems. Through the use of object-oriented mechanisms, a very general yet efficient version of the Articulated-Body (AB) algorithm has been implemented. An efficient solution to branching within chains is developed in the paper so that the algorithm can be used to compute the dynamics for the entire class of open-chain, tree-structured mechanisms. By including compliant contacts with the environment, most closed-chain systems can also be modeled. URV systems with an extended set of topologies can be simulated including proposed underwater walking machines with intra-body powered articulations. Using the encapsulation inherent in C++, the hydrodynamics code has been confined to a single class, thereby explicitly defining this framework and providing an environment for readily implementing desired hydrodynamics algorithms. Resulting simulations are very efficient and can be used in a number of applications both in the development and use of URV systems.
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    Autonomous robots 6 (1999), S. 281-292 
    ISSN: 1573-7527
    Keywords: mobile robotics ; reinforcement learning ; artificial neural networks ; simulation ; real world
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    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract We present a case study of reinforcement learning on a real robot that learns how to back up a trailer and discuss the lessons learned about the importance of proper experimental procedure and design. We identify areas of particular concern to the experimental robotics community at large. In particular, we address concerns pertinent to robotics simulation research, implementing learning algorithms on real robotic hardware, and the difficulties involved with transferring research between the two.
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    ISSN: 1573-773X
    Keywords: genetic algorithms ; neural networks ; neural network optimization ; image classification ; image reconstruction
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    Topics: Computer Science
    Notes: Abstract Automatic classification of transmission electron-microscopy images is an important step in the complex task of determining the structure of biologial macromolecules. The process of 3D reconstruction from a set of such images implies their previous classification into homogeneous image classes. In general, different classes may represent either distinct biochemical specimens or specimens from different directions of an otherwise homogenous specimen. In this paper, a neural network classification algorithm has been applied to a real-data case in which it was known a priori the existence of two differentiated views of the same specimen. Using two labeled sets as a reference, the parameters and architecture of the classifier were optimized using a genetic algorithm. The global automatic process of training and optimization is implemented using the previously described g-lvq (genetic learning vector quantization) [10] algorithm, and compared to a non-optimized version of the algorithm, Kohonen's lvq (learning vector quantization) [7]. Using a part of the sample as training set, the results presented here show an efficient (approximately 90%) average classification rate of unknown samples in two classes. Finally, the implication of this kind of automatic classification of algorithms in the determination of three dimensional structure of biological particles is discused. This paper extends the results already presented in [11], and also improves them.
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    Neural processing letters 8 (1998), S. 253-263 
    ISSN: 1573-773X
    Keywords: expert system ; genetic algorithms ; medical diagnosis ; neural networks ; rule extraction
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    Topics: Computer Science
    Notes: Abstract Recently, neural networks have been applied to many medical diagnostic problems because of their appealing properties, robustness, capability of generalization and fault tolerance. Although the predictive accuracy of neural networks may be higher than that of traditional methods (e.g., statistical methods) or human experts, the lack of explanation from a trained neural network leads to the difficulty that users would hesitate to take the advise of a black box on faith alone. This paper presents a class of composite neural networks which are trained in such a way that the values of the network parameters can be utilized to generate If-Then rules on the basis of preselected meaningful coordinates. The concepts and methods presented in the paper are illustrated through one practical example from medical diagnosis.
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    Journal of computational neuroscience 3 (1996), S. 73-82 
    ISSN: 1573-6873
    Keywords: primate retina ; simulation ; ganglion cells ; spatial vision ; hyperacuity
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    Topics: Computer Science , Medicine , Physics
    Notes: Abstract We developed a physiologically plausible model of the first steps of spatial visual information processing in the fovea of the human retina. With the predictions of this model we could support the hypothesis that, for moderate contrasts (≤ 40%), hyperacuity is mediated by the magnocellular (MC-) pathway. Despite the lower sampling density in the MC pathway, as compared to the parvocellular (PC-) pathway, the information that is transferred by the MC ganglion cells is sufficient to achieve thresholds comparable to those of human subjects in psychophysical tasks. This is a result of the much higher signal-to-noise ratio of the MC pathway cell signals. The PC pathway cells do not transfer enough information for hyperacuity thresholds.
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    ISSN: 1573-6873
    Keywords: reflex pathway ; neuronal network ; simulation ; parliamentary principle ; neural basis of behavior
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    Topics: Computer Science , Medicine , Physics
    Notes: Abstract In inactive stick insects, sensory information from the femoral chordotonal organ (fCO) about position and movement of the femur-tibia joint is transferred via local nonspiking interneurons onto extensor and flexor tibiae motoneurons. Information is processed by the interaction of antagonistic parallel pathways at two levels: (1) at the input side of the nonspiking interneurons and (2) at the input side of the motoneurons. We tested by a combination of physiological experiments and computer simulation whether the known network topology and the properties of its elements are sufficient to explain the generation of the motor output in response to passive joint movements, that is resistance reflexes. In reinvestigating the quantitative characteristics of interneuronal pathways we identified 10 distinct types of nonspiking interneurons. Synaptic inputs from fCO afferents onto these interneurons are direct excitatory and indirect inhibitory. These connections were investigated with respect to position and velocity signals from the fCO. The results were introduced in the network simulation. The motor output of the simulation has the same characteristics as the real system, even when particular types of interneurons were removed in the simulation and the real system.
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    Journal of computational neuroscience 3 (1996), S. 137-153 
    ISSN: 1573-6873
    Keywords: potassium ; compartmental ; learning ; plasticity ; simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Medicine , Physics
    Notes: Abstract We developed a multicompartmental Hodgkin-Huxley model of the Hermissenda type-B photoreceptor and used it to address the relative contributions of reductions of two K+ currents, I a and I C, to changes in cellular excitability and synaptic strength that occur in these cells after associative learning. We found that reductions of gC, the peak conductance of I C, substantially increased the firing frequency of the type-B cell during the plateau phase of a simulated light response, whereas reductions of gA had only a modest contribution to the plateau frequency. This can be understood at least in part by the contributions of these currents to the light-induced (nonspiking) generator potential, the plateau of which was enhanced by gC reductions, but not by gA reductions. In contrast, however, reductions of gA broadened the type-B cell action potential, increased Ca2+ influx, and increased the size of the postsynaptic potential produced in a type-A cell, whereas similar reductions of gC had only negligible contributions to these measures. These results suggest that reductions of I A and I C play important but different roles in type-B cell plasticity.
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    Software quality journal 6 (1997), S. 127-135 
    ISSN: 1573-1367
    Keywords: Keywords: testing ; real-time systems ; genetic algorithms ; temporal behaviour ; embedded systems
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    Topics: Computer Science
    Notes: Abstract The development of real-time systems is an essential industrial activity whose importance is increasing. The most important analytical method to assure the quality of real-time systems is dynamic testing. Testing is the only method which examines the actual run-time behaviour of real-time software, based on an execution in the real application environment. Dynamic aspects like the duration of computations, the memory actually needed, or the synchronization of parallel processes are of major importance for the correct function of real-time systems and have to be tested. A comprehensive investigation of existing software test methods shows that they mostly concentrate on testing for functional correctness. They are not suited for an examination of temporal correctness which is essential to real-time systems. Very small systems show a wide range of different execution times. Therefore, existing test procedures must be supplemented by new methods, which concentrate on determining whether the system violates its specified timing constraints. In general, this means that outputs are produced too early or their computation takes too long. The task of the tester is to find the inputs with the longest or shortest execution times to check whether they produce a temporal error. If the search for such inputs is interpreted as a problem of optimization, genetic algorithms can be used to find the inputs with the longest or shortest execution times automatically. The fitness function is the execution time measured in processor cycles. Experiments using genetic algorithms on a number of programs with up to 1511 LOC and 843 integer input parameters have successfully identified new longer and shorter paths than had been found using random testing or systematic testing. Genetic algorithms are able therefore to check large programs and they show considerable promise in establishing the validity of the temporal behaviour of real-time software.
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    Statistics and computing 6 (1996), S. 277-287 
    ISSN: 1573-1375
    Keywords: Bayesian inference ; contingency tables ; Gibbs sampling ; graphical methods ; hypothesis testing ; independence ; intraclass tables ; model comparison ; predictive densities ; quasisymmetry ; simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract In this paper we present a simulation and graphics-based model checking and model comparison methodology for the Bayesian analysis of contingency tables. We illustrate the approach by testing the hypotheses of independence and symmetry on complete and incomplete simulated tables.
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    Real-time systems 14 (1998), S. 251-267 
    ISSN: 1573-1383
    Keywords: development environment ; real-time ; scheduling ; simulation ; design tool
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    Topics: Computer Science
    Notes: Abstract The development of time critical applications needs specific tools able to cope with both functional and non-functional requirements. In this paper we describe a design and programming environment to assist the development of hard real-time applications. An interactive graphic interface is provided to facilitate the design of the application according to three hierarchical levels. The development model we propose is based on an iterative process in which the real-time scheduling support is considered from the beginning of the design phases. Our graphic environment integrates several tools to analyze, test, and simulate the real-time application under development. In particular, the tools we have implemented are: a Design Tool, to describe the structure of the application, a Schedulability Analyser Tool (SAT), to verify off-line the feasibility of the schedule of a critical task set, a Scheduling Simulator, to test the average behavior of the application, and a Maximum Execution Time (MET) estimator to bound the worst case duration of each task.
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    Journal of clinical monitoring and computing 15 (1999), S. 227-232 
    ISSN: 1573-2614
    Keywords: simulation ; problem-based learning
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    Topics: Computer Science , Medicine
    Notes: Abstract Background. We developed a problem-based learning exercise with a full-scale human patient simulator to teach residents the emergency management and differential diagnosis of acute intraoperative hypotension. Methods.We developed the exercise through the following steps: clear definition of learning objectives, preparation of an appropriate case stem, development of clinically realistic scenarios to illustrate objectives, and an interactive instructor to stimulate discussion. Results. The exercise focused on the differential diagnosis of intraoperative hypotension, and the acute treatment of hypovolemia, cardiac tamponade, tension pneumothorax, and anaphylaxis. Conclusions. Exercises on a full-scale patient simulator are a natural extension of problem-based learning. Recent research in learning theory provides the rationale for this teaching modality's potential as a learning tool.
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    Journal of clinical monitoring and computing 15 (1999), S. 481-491 
    ISSN: 1573-2614
    Keywords: Cerebral blood flow ; cerebral vascular resistance ; cerebral perfusion pressure ; PaCO2 ; PaO2 ; cerebral metabolic rate of oxygen consumption ; educational model ; simulation
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    Topics: Computer Science , Medicine
    Notes: Abstract Objective.To implement a realistic autoregulation mechanism toenhance an existing educational brain model that displays in real-time thecerebral metabolic rate (CMRO2), cerebral blood flow (CBF),cerebral blood volume (CBV), intracranial pressure (ICP), and cerebralperfusion pressure (CPP). Methods.A dynamic cerebrovascular resistance(CVR) feedback loop adjusts automatically to maintain CBF within a range ofthe CPP and defines autoregulation. The model obtains physiologic parametersfrom a full-scale patient simulator. We assumed that oxygen demand andarterial partial pressure of carbon dioxide (CO2 responsivity) arethe two major factors involved in determining CBF. In addition, our brainmodel increases oxygen extraction up to 70% once CBF becomes insufficient tosupport CMRO2. The model was validated against data from theliterature. Results.The model's response varied less than 9%from the literature data. Similarly, based on correlation coefficients betweenthe brain model and experimental data, a good fit was obtained for curvesdescribing the relationship between CBF and PaCO2 at a meanarterial blood pressure of 150 mm Hg (R2 = 0.92) and 100 mm Hg(R2 = 0.70). Discussion.The autoregulated brain model, withincorporated CO2 responsivity and a variable oxygen extraction,automatically produces changes in CVR, CBF, CBV, and ICP consistent withliterature reports, when run concurrently with a METI full-scale patientsimulator (Medical Education Technologies, Inc., Sarasota, Florida). Once themodel is enhanced to include herniation, vasospasm, and drug effects, itsutility will be expanded beyond demonstrating only basic neuroanesthesiaconcepts.
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    Journal of clinical monitoring and computing 12 (1995), S. 89-95 
    ISSN: 1573-2614
    Keywords: anesthesia ; atracurium ; closed-loop control ; drug delivery ; feedback control ; infusion protocol ; mivacurium ; neuromuscular blockade ; simulation ; vecuronium
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    Topics: Computer Science , Medicine
    Notes: Abstract Neuromuscular blockade is controlled during anesthesia by administering either bolus doses or a continuous infusion of a blocking agent. To test whether a constant infusion technique requires less attention and provides better control we used a computer to simulate neuromuscular blockade. Using the model we maintained 95% blockade with mivacurium, atracurium, and vecuronium. It required 1.2 changes per hour to maintain the blockade by continuous infusion; an average of 4.5 bolus per hour were required to maintain blockade by the bolus technique. When the bolus and continuous infusion techniques were combined, only 0.16 changes per hour were required. Atracurium was then given to ten patients during anesthesia, following the bolus plus continuous infusion protocol. After a bolus was given to obtain 100% twitch depression, for tracheal intubation, neuromuscular function was assessed by train-of-four stimulation of the ulnar or facial nerves by observing the resultant muscle movement. When the first twitch of the train-of-four returned, relaxation was maintained by continuous infusion. A bolus was given and the drug infusion rate was changed whenever the level of relaxation changed from the desired one twitch of the train-of-four. The infusion rate was adjusted only 1.12±0.79 times per hour. The desired level of muscle relaxation was easily controlled using the bolus plus continuous infusion protocol. The infusion scheme might be implemented in future drug infusion pumps.
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    Journal of clinical monitoring and computing 12 (1995), S. 105-112 
    ISSN: 1573-2614
    Keywords: modelling ; parameter estimation ; simulation ; ventilation mechanics ; data acquisition
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    Topics: Computer Science , Medicine
    Notes: Abstract Routine application of ‘rule of thumb’ parameter sets in clinical practice pushes model visions to the background, including the complete framework of assumptions, simplifications, suppositions and conditions. But: models can be a very strong tool, when applied selectively — that means, with a clear idea of destination, definition, parameter selection and verification. This article discusses universal issues of modelling — based on ventilation mechanics models in intensive care medicine.
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    Journal of clinical monitoring and computing 12 (1995), S. 231-239 
    ISSN: 1573-2614
    Keywords: gas exchange ; mechanical respiration ; model ; simulation ; ventilation mechanics
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    Topics: Computer Science , Medicine
    Notes: Abstract The mechanical respiration of intubated patients is a process which is influenced by many parameters and, through its many interactions, is extremely complex. Taken by itself the logical analysis of this complexity is extraordinarily difficult and leads very often to false conclusions. For that reason computer simulation of complex systems by means of the computer is an important tool in the analysis of these processes. Required is a model which describes the actual behavior of the system. However, it should not be overlooked that a model always describes only a portion of reality. Models having exclusively to do with ventilation mechanics or with gas exchange cannot simulate the interactions between the two. To accomplish this purpose, an improved model is necessary, including both partial processes and thereby capturing the complexity of the system. Accordingly, both ventilation mechanics and gas exchange have been integrated equally into the newly developed model for the simulation program Simu Vent. The core of the program builds a functional multicompartment model of the lungs and considers the partial processes ventilation mechanics, gas transport, gas mixing and gas exchange. Further considered are the respirator, blood circulation and peripheral compartments. The program runs under a graphical user interface, allowing its easy use. Responsible for this ease is the user's ability to interact with the program while simulation is in progress and the specially designed graphic screen mask. Comparing measured with simulated values demonstrated that the measured curve can be simulated with minimal error. Furthermore, the multicompartment model describes disruptions in distribution. Simu Vent's application is especially well advised in the description and analysis of the theoretical fundamentals of mechanical respiration. This aspect is meaningful above all in education and research, rendering these two the model's main areas of use.
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    Journal of clinical monitoring and computing 14 (1998), S. 135-140 
    ISSN: 1573-2614
    Keywords: simulation ; peripheral nerve stimulation ; neuromuscular blockade ; thumb adduction
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    Topics: Computer Science , Medicine
    Notes: Abstract Objective. To design and fabricate a device to simulate evoked thumb adduction in response to ulnar nerve stimulation. Methods. We implemented a computer-controlled, motorized thumb (TWITCHER) that responds to ulnar nerve stimulation by an unmodified peripheral nerve stimulator. Clinically realistic response patterns are generated for both depolarizing and non-depolarizing muscle relaxants and three modes of stimulation (single twitch, train-of-four, tetanus). Results. The device has been used in a full-scale patient simulator for the last six years. Discussion. TWITCHER has been well received by participants in simulation exercises including the use of neuromuscular blocking drugs.
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    Journal of clinical monitoring and computing 15 (1999), S. 17-21 
    ISSN: 1573-2614
    Keywords: Low flow anesthesia ; inhaled anesthetics ; anesthetic cost ; simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Medicine
    Notes: Abstract Introduction. Inducing general anesthesia often involves mask ventilation using high fresh gas flow (FGF) to administer anesthetic vapor prior to endotracheal intubation. A common practice is to turn the vaporizer off when the mask is removed from the patient's face to avoid room contamination (VAPOff). An alternative approach is to leave the vaporizer on and turn the FGF to minimum to reduce the amount of vapor laden gas that can enter the room (FGFOff). The objective of this study is to compare the relative induction times and vapor costs associated with each induction strategy. Methods. Each induction method was simulated using Gasman® (MedMan Simulations, Chestnut Hill, MA) for Windows assuming a 70 kg patient. To simulate a period of mask ventilation with anesthetic vapor prior to intubation, the FGF was set to 6 l/min and the isoflurane vapor concentration to 1.2% (1 MAC) for three minutes with an alveolar ventilation of 5 l/min and cardiac output of 5 l/min. For the first simulation of the intubation period (FGFOff), FGF was turned to 150 ml/min, minute ventilation was set to zero and the vaporizer setting unchanged for one minute. Initial settings were then restored and the rate of change of anesthetic vapor concentration in the circuit (Vckt) and alveolus (Valv) followed for 10 minutes along with the cost of delivered vapor (V$). For the second simulation (VAPOff), after the initial three minutes of vapor delivery, the vaporizer was set to zero, minute ventilation was set to zero and the FGF left unchanged for one minute. The initial settings were then restored and Vckt, Valv and V$ followed for ten minutes. The cost calculation was based upon a 100 ml bottle of Isoflurane at $72/bottle. Actual gas flow was measured at the y-piece of a circle system for fresh gas flows from 0.15 to 6 l/min. Results. At the end of the simulated intubation period (minute 4), Vckt was unchanged with the FGFOff method whereas it had fallen by more than half with the VAPOff method. Using VAPOff, it took until the 6-minute mark for Vckt to return to the same concentration that existed prior to intubation at minute three. Throughout the 10 minute simulated induction, Valv using FGFOff exceeded Valv using VAPOff although the difference became small at the end of the period. V$ was essentially identical at all time points. No flow into the room was measured at the minimum fresh gas flow whereas higher fresh gas flows resulted in a significant portion of the fresh gas flowing into the room. Conclusions. The strategy of turning the FGF to minimum and leaving the vaporizer on during intubation does not contaminate the room and speeds induction by fostering a greater alveolar concentration than the VAPOff method. Cost savings are derived using FGFOff since a higher alveolar concentration is achieved at the same vapor cost. Additional cost savings are demonstrated since a low flow technique is possible immediately after intubation when using FGFOff. The practice of turning off the vaporizer during endotracheal intubation while FGF remains high should be abandoned.
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    Computational optimization and applications 9 (1998), S. 275-298 
    ISSN: 1573-2894
    Keywords: timetable problem ; tabu search ; simulated annealing ; genetic algorithms
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract In this paper we present the results of an investigation of the possibilities offered by three well-known metaheuristic algorithms to solve the timetable problem, a multi-constrained, NP-hard, combinatorial optimization problem with real-world applications. First, we present our model of the problem, including the definition of a hierarchical structure for the objective function, and of the neighborhood search operators which we apply to matrices representing timetables. Then we report about the outcomes of the utilization of the implemented systems to the specific case of the generation of a school timetable. We compare the results obtained by simu lated annealing, tabu search and two versions, with and without local search, of the genetic algorithm. Our results show that GA with local search and tabu search based on temporary problem relaxations both outperform simulated annealing and handmade timetables.
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    User modeling and user adapted interaction 5 (1995), S. 67-86 
    ISSN: 1573-1391
    Keywords: Adaptive ; planning ; planning recognition ; simulation ; multi-agent ; multimedia ; tutoring ; artificial intelligence ; knowledge representation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract An intelligent tutoring system customizes its presentation of knowledge to the individual needs of each student based on a model of the student. Student models are more complex than other user models because the student is likely to have misconceptions. We have addressed several difficult issues in reasoning about a student's knowledge and skills within a real-time simulation-based training system. Our conceptual framework enables important aspects of the tutor's reasoning to be based upon simple, comprehensible representations that are the basis for a Student Centered Curriculum. We have built a system for teaching cardiac resuscitation techniques in which the decisions abouthow to teach are separated from the decisions aboutwhat to teach. The training context (i.e., choice of topics) is changed based on a tight interaction between student modeling techniques and simulation management. Although complex student models are still required to support detailed reasoning about how to teach, we argue that the decision about what to teach can be adequately supported by qualitatively simpler techniques, such as overlay models. This system was evaluated in formative studies involving medical school faculty and students. Construction of the student model involves monitoring student actions during a simulation and evaluating these actions in comparison with an expert model encoded as a multi-agent plan. The plan recognition techniques used in this system are novel and allow the expert knowledge to be expressed in a form that is natural for domain experts.
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    Real-time systems 15 (1998), S. 103-130 
    ISSN: 1573-1383
    Keywords: allocation ; mapping ; multiprocessor scheduling ; parallel systems ; distributed systems ; simulated annealing ; genetic algorithms
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This article presents and evaluates the Slack Method, a new constructive heuristic for the allocation (mapping) of periodic hard real-time tasks to multiprocessor or distributed systems. The Slack Method is based on task deadlines, in contrast with other constructive heuristics, such as List Processing. The presented evaluation shows that the Slack Method is superior to list-processing-based approaches with regard to both finding more feasible solutions as well as finding solutions with better objective function values. In a comparative survey we evaluate the Slack Method against several alternative allocation techniques. This includes comparisons with optimal algorithms, non-guided search heuristics (e.g. Simulated Annealing), and other constructive heuristics. The main practical result of the comparison is that a combination of non-guided search and constructive approaches is shown to perform better than either of them alone, especially when using the Slack Method.
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    Real-time systems 15 (1998), S. 61-90 
    ISSN: 1573-1383
    Keywords: system design ; executable specifications ; class-based modeling ; simulation ; formal methods ; model checking
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract The Production Cell example was chosen by FZI (the Computer Science Research Center), in Karlsruhe. to examine the benefits of formal methods for industrial applications. This example was implemented in more than 30 formalisms. This paper describes the implementation of the Production Cell in OBSERV. The OBSERV methodology for software development is based on rapid construction of an executable specification, or prototype, of a system, which may be examined and modified repeatedly to achieve the desired functionality. The objectives of OBSERV also include facilitating a smooth transition to a target system, and providing means for reusing specification, design, and code of systems, particularly real-time reactive systems. In this paper we show how the methods used in the OBSERV implementation address the requirements imposed by reactive systems. We describe the OBSERV implementation of the Production cell, explain design decisions, with special emphasis on reusability and safety issues. We demonstrate how to take care of safety and liveness properties required for this example. These properties are checked by means of simulation and formally proved with a model checker.
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    Statistics and computing 6 (1996), S. 85-92 
    ISSN: 1573-1375
    Keywords: Cluster analysis ; Conditional Gaussian distribution ; EM algorithm ; graphical modelling ; location model ; mixture maximum likelihood ; simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract One possible approach to cluster analysis is the mixture maximum likelihood method, in which the data to be clustered are assumed to come from a finite mixture of populations. The method has been well developed, and much used, for the case of multivariate normal populations. Practical applications, however, often involve mixtures of categorical and continuous variables. Everitt (1988) and Everitt and Merette (1990) recently extended the normal model to deal with such data by incorporating the use of thresholds for the categorical variables. The computations involved in this model are so extensive, however, that it is only feasible for data containing very few categorical variables. In the present paper we consider an alternative model, known as the homogeneous Conditional Gaussian model in graphical modelling and as the location model in discriminant analysis. We extend this model to the finite mixture situation, obtain maximum likelihood estimates for the population parameters, and show that computation is feasible for an arbitrary number of variables. Some data sets are clustered by this method, and a small simulation study demonstrates characteristics of its performance.
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    ISSN: 1573-1375
    Keywords: Bayesian networks ; genetic algorithms ; optimal decomposition ; graph triangulation ; moral graph ; NP-hard problems ; statistical analysis
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract In this paper we consider the optimal decomposition of Bayesian networks. More concretely, we examine empirically the applicability of genetic algorithms to the problem of the triangulation of moral graphs. This problem constitutes the only difficult step in the evidence propagation algorithm of Lauritzen and Spiegelhalter (1988) and is known to be NP-hard (Wen, 1991). We carry out experiments with distinct crossover and mutation operators and with different population sizes, mutation rates and selection biasses. The results are analysed statistically. They turn out to improve the results obtained with most other known triangulation methods (Kjærulff, 1990) and are comparable to results obtained with simulated annealing (Kjærulff, 1990; Kjærulff, 1992).
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    Artificial intelligence review 12 (1998), S. 265-319 
    ISSN: 1573-7462
    Keywords: genetic algorithms ; real coding ; continuous search spaces
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Genetic algorithms play a significant role, as search techniques forhandling complex spaces, in many fields such as artificial intelligence, engineering, robotic, etc. Genetic algorithms are based on the underlying genetic process in biological organisms and on the naturalevolution principles of populations. These algorithms process apopulation of chromosomes, which represent search space solutions,with three operations: selection, crossover and mutation. Under its initial formulation, the search space solutions are coded using the binary alphabet. However, the good properties related with these algorithms do not stem from the use of this alphabet; other coding types have been considered for the representation issue, such as real coding, which would seem particularly natural when tackling optimization problems of parameters with variables in continuous domains. In this paper we review the features of real-coded genetic algorithms. Different models of genetic operators and some mechanisms available for studying the behaviour of this type of genetic algorithms are revised and compared.
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    Artificial intelligence review 11 (1997), S. 343-370 
    ISSN: 1573-7462
    Keywords: lazy learning ; nearest neighbor ; genetic algorithms ; differential games ; pursuit games ; teaching ; reinforcement learning
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Combining different machine learning algorithms in the same system can produce benefits above and beyond what either method could achieve alone. This paper demonstrates that genetic algorithms can be used in conjunction with lazy learning to solve examples of a difficult class of delayed reinforcement learning problems better than either method alone. This class, the class of differential games, includes numerous important control problems that arise in robotics, planning, game playing, and other areas, and solutions for differential games suggest solution strategies for the general class of planning and control problems. We conducted a series of experiments applying three learning approaches – lazy Q-learning, k-nearest neighbor (k-NN), and a genetic algorithm – to a particular differential game called a pursuit game. Our experiments demonstrate that k-NN had great difficulty solving the problem, while a lazy version of Q-learning performed moderately well and the genetic algorithm performed even better. These results motivated the next step in the experiments, where we hypothesized k-NN was having difficulty because it did not have good examples – a common source of difficulty for lazy learning. Therefore, we used the genetic algorithm as a bootstrapping method for k-NN to create a system to provide these examples. Our experiments demonstrate that the resulting joint system learned to solve the pursuit games with a high degree of accuracy – outperforming either method alone – and with relatively small memory requirements.
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    ISSN: 1573-7497
    Keywords: object localization ; registration ; genetic algorithms ; population-based incremental learning ; computer-assisted surgery
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Object localization has applications in many areas of engineering and science. The goal is to spatially locate an arbitrarily shaped object. In many applications, it is desirable to minimize the number of measurements collected while ensuring sufficient localization accuracy. In surgery, for example, collecting a large number of localization measurements may either extend the time required to perform a surgical procedure or increase the radiation dosage to which a patient is exposed. Localization accuracy is a function of the spatial distribution of discrete measurements over an object when measurement noise is present. In previous work (J. of Image Guided Surgery, Simon et al., 1995), metrics were presented to evaluate the information available from a set of discrete object measurements. In this study, new approaches to the discrete point data selection problem are described. These include hillclimbing, genetic algorithms (GAs), and Population-Based Incremental Learning (PBIL). Extensions of the standard GA and PBIL methods that employ multiple parallel populations are explored. The results of extensive empirical testing are provided. The results suggest that a combination of PBIL and hillclimbing result in the best overall performance. A computer-assisted surgical system that incorporates some of the methods presented in this paper is currently being evaluated in cadaver trials.
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    Applied intelligence 8 (1998), S. 73-84 
    ISSN: 1573-7497
    Keywords: Evolutionary computation ; genetic algorithms ; neural networks ; genetic programming
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Evolutionary computation is a class of global search techniques based on the learning process of a population of potential solutions to a given problem, that has been successfully applied to a variety of problems. In this paper a new approach to the construction of neural networks based on evolutionary computation is presented. A linear chromosome combined to a graph representation of the network are used by genetic operators, which allow the evolution of the architecture and the weights simultaneously without the need of local weight optimization. This paper describes the approach, the operators and reports results of the application of this technique to several binary classification problems.
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    Applied intelligence 8 (1998), S. 33-41 
    ISSN: 1573-7497
    Keywords: genetic programming ; genetic algorithms ; computational genetics ; machine learning ; adaptive systems ; mobile robot ; robotics ; robot ; wall-following
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This paper demonstrates the use of genetic programming (GP) for the development of mobile robot wall-following behaviors. Algorithms are developed for a simulated mobile robot that uses an array of range finders for navigation. Navigation algorithms are tested in a variety of differently shaped environments to encourage the development of robust solutions, and reduce the possibility of solutions based on memorization of a fixed set of movements. A brief introduction to GP is presented. A typical wall-following robot evolutionary cycle is analyzed, and results are presented. GP is shown to be capable of producing robust wall-following navigation algorithms that perform well in each of the test environments used.
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    Applied intelligence 8 (1998), S. 113-121 
    ISSN: 1573-7497
    Keywords: genetic algorithms ; neural networks ; pole-cart system ; neuro-controller ; simulation ; gene activation ; multi-level chromosome
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This paper describes the application of the Structured Genetic Algorithm (sGA) to design neuro-controllers for an unstable physical system. In particular, the approach uses a single unified genetic process to automatically evolve complete neural nets (both architectures and their weights) for controlling a simulated pole-cart system. Experimental results demonstrate the effectiveness of the sGA-evolved neuro-controllers for the task—to keep the pole upright (within a specified vertical angle) and the cart within the limits of the given track.
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    Applied intelligence 9 (1998), S. 7-23 
    ISSN: 1573-7497
    Keywords: intelligent vehicles ; evolutionary algorithms ; simulation ; distributed AI
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Recent research in automated highway systems has ranged from low-level vision-based controllers to high-level route-guidance software. However, there is currently no system for tactical-level reasoning. Such a system should address tasks such as passing cars, making exits on time, and merging into a traffic stream. Many previous approaches have attempted to hand construct large rule-based systems which capture the interactions between multiple input sensors, dynamic and potentially conflicting subgoals, and changing roadway conditions. However, these systems are extremely difficult to design due to the large number of rules, the manual tuning of parameters within the rules, and the complex interactions between the rules. Our approach to this intermediate-level planning is a system which consists of a collection of autonomous agents, each of which specializes in a particular aspect of tactical driving. Each agent examines a subset of the intelligent vehicle's sensors and independently recommends driving decisions based on their local assessment of the tactical situation. This distributed framework allows different reasoning agents to be implemented using different algorithms. When using a collection of agents to solve a single task, it is vital to carefully consider the interactions between the agents. Since each reasoning object contains several internal parameters, manually finding values for these parameters while accounting for the agents' possible interactions is a tedious and error-prone task. In our system, these parameters, and the system's overall dependence on each agent, is automatically tuned using a novel evolutionary optimization strategy, termed Population-Based Incremental Learning (PBIL). Our system, which employs multiple automatically trained agents, can competently drive a vehicle, both in terms of the user-defined evaluation metric, and as measured by their behavior on several driving situations culled from real-life experience. In this article, we describe a method for multiple agent integration which is applied to the automated highway system domain. However, it also generalizes to many complex robotics tasks where multiple interacting modules must simultaneously be configured without individual module feedback.
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    Autonomous robots 5 (1998), S. 199-213 
    ISSN: 1573-7527
    Keywords: adaptive behaviors ; evolutionary robots ; fractal fitness landscape ; robot navigation ; genetic algorithms ; over-adaptation ; developed neural network
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract An autonomous robot “Khepera” was simulated with a sensory-motor model, which evolves in the genetic algorithm (GA) framework, with the fitness evaluation in terms of the navigation performance in a maze course. The sensory-motor model is a developed neural network decoded from a graph-represented chromosome, which is evolved in the GA process with several genetic operators. It was found that the fitness landscape is very rugged when it is observed at the starting point of the course. A hypothesis for this ruggedness is proposed, and is supported by the measurement of fractal dimension. It is also observed that the performance is sometimes plagued by “Loss of Robustness,” after the robot makes major evolutionary jumps. Here, the robustness is quantitatively defined as a ratio of the averaged fitness of the evolved robot navigating in perturbed environments over the fitness of the evolved robot in the referenced environment. Possible explanation of robustness loss is the over-adaptation occurred in the environment where the evolution was taken place. Testing some other possibilities for this loss of robustness, many simulation experiments were conducted which smooth out the discrete factors in the model and environment. It was found that smoothing the discrete factors does not solve the loss of robustness. An effective method for maintaining the robustness is the use of averaged fitness over different navigation conditions. The evolved models in the simulated environment were tested by down-loading the models into the real Khepera robot. It is demonstrated that the tendency of fitness values observed in the simulation were adequately regenerated.
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