Technical Note: \cal Q-Learning
Machine Learning
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Co-operative Reinforcement Learning By Payoff Filters (Extended Abstract)
ECML '95 Proceedings of the 8th European Conference on Machine Learning
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
Construction of a learning agent handling its rewards according to environmental situations
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3
Utility based Q-learning to facilitate cooperation in Prisoner's Dilemma games
Web Intelligence and Agent Systems
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When we construct an agent by integrating modules, there appear troubles concerning the autonomy of the agent if we introduce a heuristics that dominates the whole agent. Thus, we design an agent that has an interdependent heuristics influenced by a module controlled by the heuristics, and we apply these agents into a problem of obtaining cooperation of Multi-Agents. We enable a present method that can solve the problem in a reinforcement learning context to be applied into a dynamic environment, and the improved method is embodied into the agent as the interdependent heuristics. We conduct experiments comparing the proposed agents with agents such as those ones each of which has a heuristics controlled by a supervisor, then we empirically confirm that the proposed agent having the interdependent heuristics is the most flexible of all the tested agent.