Now showing items 1-2 of 2

    • All learning is local: Multi-agent learning in global reward games 

      Chang, Yu-Han; Ho, Tracey; Kaelbling, Leslie P. (2004-01)
      In large multiagent games, partial observability, coordination, and credit assignment persistently plague attempts to design good learning algorithms. We provide a simple and efficient algorithm that in part uses a linear ...
    • Playing is believing: the role of beliefs in multi-agent learning 

      Chang, Yu-Han; Kaelbling, Leslie P. (2003-01)
      We propose a new classification for multi-agent learning algorithms, with each league of players characterized by both their possible strategies and possible beliefs. Using this classification, we review the optimality of ...