Online learning about other agents in a dynamic multiagent system
AGENTS '98 Proceedings of the second international conference on Autonomous agents
The dynamics of reinforcement learning in cooperative multiagent systems
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Bidding in reinforcement learning: a paradigm for multi-agent systems
Proceedings of the third annual conference on Autonomous Agents
Learning Team Strategies: Soccer Case Studies
Machine Learning
Multi-agent reinforcement learning: weighting and partitioning
Neural Networks
Neuro-Dynamic Programming
Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Dynamic Programming
Co-Learning and the Evolution of Social Acitivity
Co-Learning and the Evolution of Social Acitivity
Value-function reinforcement learning in Markov games
Cognitive Systems Research
Editorial: Individual action and collective function: From sociology to multi-agent learning
Cognitive Systems Research
On fairness and learning agents in a bargaining model with uncertainty
Cognitive Systems Research
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This paper investigates the effect of different rationality assumptions on the performance of co-learning by multiple agents in extensive games. Extensive games involve sequences of steps and close interactions between agents, and are thus more difficult than more commonly investigated (one-step) strategic games. Rationality assumptions may thus have more complicated influences on learning, e.g., improving performance sometimes while hurting performance some other times. In testing different levels of rationality assumptions, a "double estimation" method for reinforcement learning suitable for extensive games is developed, whereby an agent learns not only its own value function but also those of other agents. Experiments based on such a reinforcement learning method are carried out using several typical examples of games. Our results indeed showed a complex pattern of effects resulting from (different levels of) rationality assumptions.