Artificial intelligence and tutoring systems: computational and cognitive approaches to the communication of knowledge
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Artificial intelligence: a modern approach
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An efficient mapping of fuzzy ART onto a neural architecture
Neural Networks
An Introduction to Genetic Algorithms
An Introduction to Genetic Algorithms
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
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IEEE Transactions on Knowledge and Data Engineering
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Machine Learning
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ICAL 2003 Proceedings of the eighth international conference on Artificial life
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IAT '05 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
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IAT '05 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Hybrid negotiation for resource coordination in multiagent systems
Web Intelligence and Agent Systems
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Web Intelligence and Agent Systems
State space segmentation for acquisition of agent behavior
Web Intelligence and Agent Systems
Itinerary determination of imprecise mobile agents with firm deadline
Web Intelligence and Agent Systems
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We present a method to acquire rules for agent behavior, where continuous numeric percepts are classified into categories by fuzzy ART and fuzzy Q-learning is employed to acquire rules. To make fuzzy ART be fit for fuzzy Q-learning, we modify fuzzy ART such that it selects multiple categories for a percept vector and calculate their fitness values. For efficient learning, we also implement category integration that integrates two categories into one in order to reduce the number of categories. Moreover, we modify the choice function to be fit for our modified fuzzy ART and also modify the timing of category integration for efficient learning. Experimental results show that our method acquires good rules for agent behavior more efficiently than Q-learning with fuzzy ART.