SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Multi-criteria Reinforcement Learning
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Intra-Option Learning about Temporally Abstract Actions
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
State Space Construction for Behavior Acquisition in Multi Agent Environments with Vision and Action
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
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An extended value function is discussed in the context of multiple behavior coordination, especially in a dynamically changing multiagent environment. Unlike the traditional weighted sum of several reward functions, we define a vectorized value function which evaluates the current action strategy by introducing a discounted matrix to integrate several reward functions. Owing to the extension of the value function, the learning robot can estimate the future multiple rewards from the environment appropriately not suffering from the weighting problem. The proposed method is applied to a simplified soccer game. Computer simulations are shown and a discussion is given.