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 ...
Optimization of performance in collective systems often requires altruism. The emergence and stabilization of altruistic behaviors are dicult to achieve because the agents incur ...
As learning agents move from research labs to the real world, it is increasingly important that human users, including those without programming skills, be able to teach agents de...
The problem of reinforcement learning in large factored Markov decision processes is explored. The Q-value of a state-action pair is approximated by the free energy of a product o...
In this paper, we focus on the coordination issues in a multiagent setting. Two coordination algorithms based on reinforcement learning are presented and theoretically analyzed. O...