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  • 1
    ISSN: 0885-6125
    Keywords: Reinforcement Learning ; Curse of Dimensionality ; Learning Control ; Robotics ; kd-trees
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Parti-game is a new algorithm for learning feasible trajectories to goal regions in high dimensional continuous state-spaces. In high dimensions it is essential that neither planning nor exploration occurs uniformly over a state-space. Parti-game maintains a decision-tree partitioning of state-space and applies techniques from game-theory and computational geometry to efficiently and adaptively concentrate high resolution only on critical areas. The current version of the algorithm is designed to find feasible paths or trajectories to goal regions in high dimensional spaces. Future versions will be designed to find a solution that optimizes a real-valued criterion. Many simulated problems have been tested, ranging from two-dimensional to nine-dimensional state-spaces, including mazes, path planning, non-linear dynamics, and planar snake robots in restricted spaces. In all cases, a good solution is found in less than ten trials and a few minutes.
    Type of Medium: Electronic Resource
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  • 2
    ISSN: 0885-6125
    Keywords: Reinforcement Learning ; Curse of Dimensionality ; Learning Control ; Robotics ; kd-trees
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Parti-game is a new algorithm for learning feasible trajectories to goal regions in high dimensional continuous state-spaces. In high dimensions it is essential that neither planning nor exploration occurs uniformly over a state-space. Parti-game maintains a decision-tree partitioning of state-space and applies techniques from game-theory and computational geometry to efficiently and adaptively concentrate high resolution only on critical areas. The current version of the algorithm is designed to find feasible paths or trajectories to goal regions in high dimensional spaces. Future versions will be designed to find a solution that optimizes a real-valued criterion. Many simulated problems have been rested, ranging from two-dimensional to nine-dimensional state-spaces, including mazes, path planning, non-linear dynamics, and planar snake robots in restricted spaces. In all cases, a good solution is found in less than ten trials and a few minutes.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    [s.l.] : Macmillian Magazines Ltd.
    Nature 401 (1999), S. 356-360 
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] Climate variability in the Indian Ocean region seems to be, in some aspects, independent of forcing by external phenomena such as the El Niño/Southern Oscillation. But the extent to which, and how, internal coupled ocean–atmosphere dynamics determine the state of the Indian Ocean ...
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  • 4
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    Boston : Periodicals Archive Online (PAO)
    Business History Review. 61:4 (1987:Winter) 672 
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    Artificial intelligence review 11 (1997), S. 11-73 
    ISSN: 1573-7462
    Keywords: locally weighted regression ; LOESS ; LWR ; lazy learning ; memory-based learning ; least commitment learning ; distance functions ; smoothing parameters ; weighting functions ; global tuning ; local tuning ; interference
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This paper surveys locally weighted learning, a form of lazy learning and memory-based learning, and focuses on locally weighted linear regression. The survey discusses distance functions, smoothing parameters, weighting functions, local model structures, regularization of the estimates and bias, assessing predictions, handling noisy data and outliers, improving the quality of predictions by tuning fit parameters, interference between old and new data, implementing locally weighted learning efficiently, and applications of locally weighted learning. A companion paper surveys how locally weighted learning can be used in robot learning and control.
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  • 6
    Electronic Resource
    Electronic Resource
    Springer
    Artificial intelligence review 11 (1997), S. 75-113 
    ISSN: 1573-7462
    Keywords: locally weighted regression ; LOESS ; LWR ; lazy learning ; memory-based learning ; least commitment learning ; forward models ; inverse models ; linear quadratic regulation (LQR) ; shifting setpoint algorithm ; dynamic programming
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Lazy learning methods provide useful representations and training algorithms for learning about complex phenomena during autonomous adaptive control of complex systems. This paper surveys ways in which locally weighted learning, a type of lazy learning, has been applied by us to control tasks. We explain various forms that control tasks can take, and how this affects the choice of learning paradigm. The discussion section explores the interesting impact that explicitly remembering all previous experiences has on the problem of learning to control.
    Type of Medium: Electronic Resource
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  • 7
    Electronic Resource
    Electronic Resource
    Springer
    Artificial intelligence review 11 (1997), S. 193-225 
    ISSN: 1573-7462
    Keywords: lazy learning ; model selection ; cross validation ; optimization ; attribute selection
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Given a set of models and some training data, we would like to find the model that best describes the data. Finding the model with the lowest generalization error is a computationally expensive process, especially if the number of testing points is high or if the number of models is large. Optimization techniques such as hill climbing or genetic algorithms are helpful but can end up with a model that is arbitrarily worse than the best one or cannot be used because there is no distance metric on the space of discrete models. In this paper we develop a technique called “racing” that tests the set of models in parallel, quickly discards those models that are clearly inferior and concentrates the computational effort on differentiating among the better models. Racing is especially suitable for selecting among lazy learners since training requires negligible expense, and incremental testing using leave-one-out cross validation is efficient. We use racing to select among various lazy learning algorithms and to find relevant features in applications ranging from robot juggling to lesion detection in MRI scans.
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  • 8
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] A cholecystokinin (CCK)-inactivating peptidase was purified and identified as a membrane-bound isoform of tripeptidyl peptidase II (EC 3.4.14.10), a cytosolic subtilisin-like peptidase of previously unknown functions. The peptidase was found in neurons responding to cholecystokinin, as well as in ...
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  • 9
    ISSN: 1573-9368
    Keywords: transgenic subterranean clover ; seed protein gene ; leaf expression ; sulphur-rich protein
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract A gene encoding a sulphur-rich, sunflower seed albumin (23% cysteine plus methionine) was modified to contain the promoter for the 35S RNA of cauliflower mosaic virus, in order to obtain leaf expression in transgenic plants. In addition, a sequence encoding an endoplasmic reticulum-retention signal was added to the 3′ end of the coding region so as to stabilize the protein by diverting it away from the vacuole. The modified gene was introduced into subterranean clover (T. subterraneum L.) and its expression was detected by northern and western blots and by immunogold localization. The albumin was accumulated in the lumen of the endoplasmic reticulum, and, among six independent, transformed lines, it accumulated in the leaves of T0 transgenic plants at varying levels up to 0.3% of the total extractable protein. The level of accumulation of the sunflower albumin increased with increasing leaf age, and in the older leaves of the most highly expressing plants of the T1 generation it reached 1.3% of total extractable protein. Expression of the SSA gene was stable in the first and second generation progeny. These results indicate that there is potential for significantly improving the nutritional value of subterranean clover for ruminant animals such as sheep by expressing genes that code for sulphur-rich, rumen-stable proteins in leaves.
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  • 10
    ISSN: 1040-0397
    Keywords: Pyrroloquinoline quinone ; Polyamines ; Immobilization ; Biosensor ; Thiol ; Chemistry ; Polymer and Materials Science
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Pyrroloquinoline quinone (PQQ) was immobilized on gold electrodes by prior adsorption of the polyamines polyethylenimine, and triethylene tetraamine, followed by carbodiimide coupling of PQQ to the surface-adsorbed amine groups. The stability and electrochemical behavior of the electrodes, in which the amino-containing linker molecule is adsorbed on the electrode surface, were compared with those of electrodes prepared by carbodiimide coupling of PQQ to a cystamine monolayer, in which the sulfur-containing linker molecule is associated with the gold surface. The electrodes prepared using adsorbed polyethylenimine showed comparable stability to those based on a cystamine monolayer, but reveal enhanced stability to application of negative potentials (〈 -1.1 V). The method provides an alternative to the conventional functionalization of Au electrodes by thiols.
    Additional Material: 4 Ill.
    Type of Medium: Electronic Resource
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