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Titlebook: Anticipatory Learning Classifier Systems; Martin V. Butz Book 2002 Springer Science+Business Media New York 2002 agents.algorithms.behavio

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樓主: microbe
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發(fā)表于 2025-3-23 09:50:27 | 只看該作者
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發(fā)表于 2025-3-23 16:30:24 | 只看該作者
Experiments with ACS2,oo weak, which would result in a larger, still over-specialized population. It is examined if the GA is able to overcome the observed over-specialization. Does the GA result in an evolution of accurate, maximally general classifiers in the population and further, does the GA cause a convergence to the aspired classifiers?
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發(fā)表于 2025-3-23 19:01:51 | 只看該作者
Limits,remedy the possibly occurring over-specializations in the ALP. The result was a decrease in population size and model size and a consequent decrease in computation time and the evolution of an even better environmental model. Moreover, the reinforcement learning capabilities of ACS2 were shown in the multiplexer and the maze environment.
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發(fā)表于 2025-3-24 00:28:52 | 只看該作者
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發(fā)表于 2025-3-24 03:43:05 | 只看該作者
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發(fā)表于 2025-3-24 09:42:17 | 只看該作者
Book 2002hat autonomously build anticipatory environmental models. An anticipatory model specifies all possible action-effects in an environment with respect to given situations. It can be used to simulate anticipatory adaptive behavior. ..Anticipatory Learning Classifier Systems. highlights how anticipation
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發(fā)表于 2025-3-24 12:50:00 | 只看該作者
1568-2587 ons, and adaptive behavior beyond reinforcement learning. ..Anticipatory Learning Classifier Systems. gives a detailed algorithmic description as well as a prog978-1-4613-5290-7978-1-4615-0891-5Series ISSN 1568-2587
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發(fā)表于 2025-3-24 16:56:54 | 只看該作者
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