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  • Articles  (12)
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  • evolution
  • Springer  (12)
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  • Naturalis Biodiversity Center
  • Computer Science  (12)
  • 1
    Electronic Resource
    Electronic Resource
    Dominance hierarchies and the evolution of human reasoning (1996)
    Springer
    Minds and machines 6 (1996), S. 463-480 
    Details
    ISSN: 1572-8641
    Keywords: Human reasoning ; evolution ; deontic reasoning ; transitive reasoning ; non-human primates ; neocortical ratio ; dominance hierarchy
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Philosophy
    Notes: Abstract Research from ethology and evolutionary biology indicates the following about the evolution of reasoning capacity. First, solving problems of social competition and cooperation have direct impact on survival rates and reproductive success. Second, the social structure that evolved from this pressure is the dominance hierarchy. Third, primates that live in large groups with complex dominance hierarchies also show greater neocortical development, and concomitantly greater cognitive capacity. These facts suggest that the necessity of reasoning effectively about dominance hierarchies left an indelible mark on primate reasoning architectures, including that of humans. In order to survive in a dominance hierarchy, an individual must be capable of (a) making rank discriminations, (b) recognizing what is forbidden and what is permitted based one's rank, and (c) deciding whether to engage in or refriin from activities that will allow one to move up in rank. The first problem is closely tied to the capacity for transitive reasoning, while the second and third are intimately related to the capacity for deontic reasoning. I argue that the human capacity for these types of reasoning have evolutionary roots that reach deeper into our ancestral past than the emergence of the hominid line, and the operation of these evolutionarily primitive reasoning systems can be seen in the development of human reasoning and domain-specific effects in adult reasoning.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00389654
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  • 2
    Electronic Resource
    Electronic Resource
    Syntax as an Emergent Characteristic of the Evolution of Semantic Complexity (1999)
    Springer
    Minds and machines 9 (1999), S. 309-346 
    Details
    ISSN: 1572-8641
    Keywords: language ; grammar ; syntax ; semantics ; evolution ; emergence ; brain size
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Philosophy
    Notes: Abstract It is commonly argued that the rules of language, as distinct from its semantic features, are the characteristics which most clearly distinguish language from the communication systems of other species. A number of linguists (e.g., Chomsky 1972, 1980; Pinker 1994) have suggested that the universal features of grammar (UG) are unique human adaptations showing no evolutionary continuities with any other species. However, recent summaries of the substantive features of UG are quite remarkable in the very general nature of the features proposed. While the syntax of any given language can be quite complex, the specific rules vary so much between languages that the truly universal (i.e. innate) aspects of grammar are not complex at all. In fact, these features most closely resemble a set of general descriptions of our richly complex semantic cognition, and not a list of specific rules. General principles of the evolutionary process suggest that syntax is more properly understood as an emergent characteristic of the explosion of semantic complexity that occurred during hominid evolution. It is argued that grammatical rules used in given languages are likely to be simply conventionalized, invented features of language, and not the result of an innate, grammar-specific module. The grammatical and syntactic regularities that are found across languages occur simply because all languages attempt to communicate the same sorts of semantic information.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008360020568
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  • 3
    Electronic Resource
    Electronic Resource
    Integrating neuroscience, psychology, and evolutionary biology through a teleological conception of function (1996)
    Springer
    Minds and machines 6 (1996), S. 481-505 
    Details
    ISSN: 1572-8641
    Keywords: Neuroscience ; evolutionary psychology ; interfield theory ; evolution ; teleology ; function ; functionalism ; brain mapping ; language processing
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Philosophy
    Notes: Abstract The idea of integrating evolutionary biology and psychology has great promise, but one that will be compromised if psychological functions are conceived too abstractly and neuroscience is not allowed to play a contructive role. We argue that the proper integration of neuroscience, psychology, and evolutionary biology requires a telelogical as opposed to a merely componential analysis of function. A teleological analysis is required in neuroscience itself; we point to traditional and curent research methods in neuroscience, which make critical use of distinctly teleological functional considerations in brain cartography. Only by invoking teleological criteria can researchers distinguish the fruitful ways of identifying brain components from the myriad of possible ways. One likely reason for reluctance to turn to neuroscience is fear of reduction, but we argue that, in the context of a teleological perspective on function, this concern is misplaced. Adducing such theoretical considerations as top-down and bottom-up constraints on neuroscientific and psychological models, as well as existing cases of productive, multidisciplinary cooperation, we argue that integration of neuroscience into psychology and evolutionary biology is likely to be mutually beneficial. We also show how it can be accommodated methodologically within the framework of an interfield theory.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00389655
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  • 4
    Electronic Resource
    Electronic Resource
    A Model for the Dynamic Interaction Between Evolution and Learning (1999)
    Springer
    Neural processing letters 10 (1999), S. 181-193 
    Details
    ISSN: 1573-773X
    Keywords: evolution ; learning ; ontogeny ; neural development ; structure optimization
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract The interaction between learning and evolution has elicited much interest particularly among researchers who use evolutionary algorithms for the optimization of neural structures. In this article, we will propose an extension of the existing models by including a developmental phase – a growth process – of the neural network. In this way, we are able to examine the dynamical interaction between genetic information and information learned during development. Several measures are proposed to quantitatively examine the benefits and the effects of such an overlap between learning and evolution. The proposed model, which is based on the recursive encoding method for structure optimization of neural networks, is applied to the problem domain of time series prediction. Furthermore, comments are made on problem domains which associate growing networks (size) during development with problems of increasing complexity.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1018724306675
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  • 5
    Electronic Resource
    Electronic Resource
    Amalthaea: An Evolving Multi-Agent Information Filtering and Discovery System for the WWW (1998)
    Springer
    Autonomous agents and multi-agent systems 1 (1998), S. 59-88 
    Details
    ISSN: 1573-7454
    Keywords: agents ; evolution ; information filtering ; world wide web
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Amalthaea is an evolving, multi-agent ecosystem for personalized filtering, discovery, and monitoring of information sites. Amalthaea's primary application domain is the World Wide Web and its main purpose is to assist its users in finding interesting information. Two different categories of agents are introduced in the system: filtering agents that model and monitor the interests of the user and discovery agents that model the information sources.A market-like ecosystem where the agents evolve, compete, and collaborate is presented: agents that are useful to the user or other agents reproduce, while low-performing agents are destroyed. Results from various experiments with different system configurations and varying ratios of user interests versus agents in the system are presented. Finally issues like fine-tuning the initial parameters of the system and establishing and maintaining equilibria in the ecosystem are discussed.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1010094506174
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  • 6
    Electronic Resource
    Electronic Resource
    Domain-oriented design environments (1994)
    Springer
    Automated software engineering 1 (1994), S. 177-203 
    Details
    ISSN: 1573-7535
    Keywords: automatic programming ; cooperative problem solving ; co-evolution of specification and construction ; critiquing ; design ; domain-oriented design environments ; design rationale ; end-user modifiability ; evolution ; FRAMER ; formal specifications ; JANUS ; knowledge-based software assistant ; languages of doing ; software reuse and redesign ; stakeholders ; upstream and downstream activities
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract The field of knowledge-based software engineering has been undergoing a shift in emphasis from automatic programming to human augmentation and empowerment. In our research work, we support this shift with an approach that embedshuman-computer cooperative problem-solving tools intodomain-oriented, knowledge-based design environments. Domain orientation reduces the large conceptual distance between problem-domain semantics and software artifacts. Integrated environments support the coevolution of specification and construction while allowing designers to access relevant knowledge at each stage within the software development process. This paper argues thatdomain-oriented design environments (DODEs) are complementary to the approaches pursued withknowledge-based software assistant systems (KBSAs). The DODE extends the KBSA framework by emphasizing a human-centered and domain-oriented approach facilitating communication about evolving systems among all stakeholders. The paper discusses the major challenges for software systems, develops a conceptual framework to address these problems, illustrates DODE with two examples, and assesses the contributions of the KBSA and DODE approaches toward solving these problems.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00872289
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  • 7
    Electronic Resource
    Electronic Resource
    Online Interactive Neuro-evolution (2000)
    Springer
    Neural processing letters 11 (2000), S. 29-38 
    Details
    ISSN: 1573-773X
    Keywords: evolution ; online ; game ; neural ; network ; genetic ; real-time
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract In standard neuro-evolution, a population of networks is evolved in a task, and the network that best solves the task is found. This network is then fixed and used to solve future instances of the problem. Networks evolved in this way do not handle real-time interaction very well. It is hard to evolve a solution ahead of time that can cope effectively with all the possible environments that might arise in the future and with all the possible ways someone may interact with it. This paper proposes evolving feedforward neural networks online to create agents that improve their performance through real-time interaction. This approach is demonstrated in a game world where neural-network-controlled individuals play against humans. Through evolution, these individuals learn to react to varying opponents while appropriately taking into account conflicting goals. After initial evaluation offline, the population is allowed to evolve online, and its performance improves considerably. The population not only adapts to novel situations brought about by changing strategies in the opponent and the game layout, but it also improves its performance in situations that it has already seen in offline training. This paper will describe an implementation of online evolution and shows that it is a practical method that exceeds the performance of offline evolution alone.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1009615730125
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  • 8
    Electronic Resource
    Electronic Resource
    Evolution and Analysis of Model CPGs for Walking: II. General Principles and Individual Variability (1999)
    Springer
    Journal of computational neuroscience 7 (1999), S. 119-147 
    Details
    ISSN: 1573-6873
    Keywords: central pattern generators ; dynamical modules ; computational neuroethology ; walking ; biomechanics ; evolution ; dynamical systems theory
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Medicine , Physics
    Notes: Abstract Are there general principles for pattern generation? We examined this question by analyzing the operation of large populations of evolved model central pattern generators (CPGs) for walking. Three populations of model CPGs were evolved, containing three, four, or five neurons. We identified six general principles. First, locomotion performance increased with the number of interneurons. Second, the top 10 three-, four-, and five-neuron CPGs could be decomposed into dynamical modules, an abstract description developed in a companion article. Third, these dynamical modules were multistable: they could be switched between multiple stable output configurations. Fourth, the rhythmic pattern generated by a CPG could be understood as a closed chain of successive destabilizations of one dynamical module by another. A combinatorial analysis enumerated the possible dynamical modular structures. Fifth, one-dimensional modules were frequently observed and, in some cases, could be assigned specific functional roles. Finally, dynamic dynamical modules, in which the modular structure itself changed over one cycle, were frequently observed. The existence of these general principles despite significant variability in both patterns of connectivity and neural parameters was explained by degeneracy in the maps from neural parameters to neural dynamics to behavior to fitness. An analysis of the biomechanical properties of the model body was essential for relating neural activity to behavior. Our studies of evolved model circuits suggest that, in the absence of other constraints, there is no compelling reason to expect neural circuits to be functionally decomposable as the number of interneurons increase. Analyzing idealized model pattern generators may be an effective methodology for gaining insights into the operation of biological pattern generators.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008920021246
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  • 9
    Electronic Resource
    Electronic Resource
    An Evolutionary Solution to Anesthesia Automated Record Keeping (1998)
    Springer
    Journal of clinical monitoring and computing 14 (1998), S. 421-424 
    Details
    ISSN: 1573-2614
    Keywords: Automated record keeper ; evolution ; management of risk ; object-oriented
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Medicine
    Notes: Abstract In the course of five years the development of an automated anesthesia record keeper has evolved through nearly a dozen stages, each marked by new features and sophistication. Commodity PC hardware and software minimized development costs. Object oriented analysis, programming and design supported the process of change. In addition, we developed an evolutionary strategy that optimized motivation, risk management, and maximized return on investment. Besides providing record keeping services, the system supports educational and research activities and through a flexible plotting paradigm, supports each anesthesiologist's focus on physiological data during and after anesthesia.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1009927928593
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  • 10
    Electronic Resource
    Electronic Resource
    The Constructibility of Artificial Intelligence (as Defined by the Turing Test) (2000)
    Springer
    Journal of logic, language and information 9 (2000), S. 419-424 
    Details
    ISSN: 1572-9583
    Keywords: Artificial Intelligence ; computability ; constructibility ; culture ; evolution ; society ; symbol grounding ; Turing ; Turing Machine ; Turing Test
    Source: Springer Online Journal Archives 1860-2000
    Topics: Linguistics and Literary Studies , Computer Science
    Notes: Abstract The Turing Test (TT), as originally specified, centres on theability to perform a social role. The TT can be seen as a test of anability to enter into normal human social dynamics. In this light itseems unlikely that such an entity can be wholly designed in an“off-line” mode; rather a considerable period of training insitu would be required. The argument that since we can pass the TT,and our cognitive processes might be implemented as a Turing Machine(TM), that consequently a TM that could pass the TT could be built, isattacked on the grounds that not all TMs are constructible in a plannedway. This observation points towards the importance of developmentalprocesses that use random elements (e.g., evolution), but in these casesit becomes problematic to call the result artificial. This hasimplications for the means by which intelligent agents could bedeveloped.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008363224791
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  • 11
    Electronic Resource
    Electronic Resource
    Learning and Evolution (1999)
    Springer
    Autonomous robots 7 (1999), S. 89-113 
    Details
    ISSN: 1573-7527
    Keywords: learning ; evolution ; plastic individuals ; Baldwin Effect
    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 the last few years several researchers have resorted to artificial evolution (e.g., genetic algorithms) and learning techniques (e.g., neural networks) for studying the interaction between learning and evolution. These studies have been conducted for two different purposes: (a) looking at the performance advantages obtained by combining these two adaptive techniques; (b) understanding the role of the interaction between learning and evolution in biological organisms. In this paper we describe some of the most representative experiments conducted in this area and point out their implications for both perspectives outlined above. Understanding the interaction between learning and evolution is probably one of the best examples in which computational studies have shed light on problems that are difficult to study with the research tools employed by evolutionary biology and biology in general. From an engineering point of view, the most relevant results are those showing that adaptation in dynamic environments gains a significant advantage by the combination of evolution and learning. These studies also show that the interaction between learning and evolution deeply alters the evolutionary and the learning process themselves, offering new perspectives from a biological point of view. The study of learning within an evolutionary perspective is still in its infancy and in the forthcoming years it will produce an enormous impact on our understanding of how learning and evolution operate.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008973931182
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  • 12
    Electronic Resource
    Electronic Resource
    Seeding, Evolutionary Growth and Reseeding: Constructing, Capturing and Evolving Knowledge in Domain-Oriented Design Environments (1998)
    Springer
    Automated software engineering 5 (1998), S. 447-464 
    Details
    ISSN: 1573-7535
    Keywords: design ; domain-oriented design environments ; evolution ; end-user modification ; knowledge construction ; computer network design
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract We live in a world characterized by evolution—that is, by ongoing processes of development, formation, and growth in both natural and human-created systems. Biology tells us that complex, natural systems are not created all at once but must instead evolve over time. We are becoming increasingly aware that evolutionary processes are ubiquitous and critical for technological innovations as well. This is particularly true for complex software systems because these systems do not necessarily exist in a technological context alone but instead are embedded within dynamic human organizations. The Center for LifeLong Learning and Design (L3D) at the University of Colorado has been involved in research on software design and other design domains for more than a decade. We understand software design as an evolutionary process in which system requirements and functionality are determined through an iterative process of collaboration among multiple stakeholders, rather than being completely specified before system development occurs. Our research focuses on the following claims about software systems embedded within dynamic human organizations: (1) they must evolve because they cannot be completely designed prior to use, (2) they must evolve to some extent at the hands of the users, and (3) they must be designed for evolution. Our theoretical work builds upon our existing knowledge of design processes and focuses on a software process model and architecture specifically for systems that must evolve. Our theories are instantiated and assessed through the development and evolution of domain-oriented design environments (DODEs)—software systems that support design activities within particular domains and that are built specifically to evolve.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1008657429810
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