We consider online learning in repeated decision problems, within the framework of a repeated game against an arbitrary opponent. For repeated matrix games, well known results esta...
Planning how to interact against bounded memory and unbounded memory learning opponents needs different treatment. Thus far, however, work in this area has shown how to design pla...
Game theoretic models of learning which are based on the strategic form of the game cannot explain learning in games with large extensive form. We study learning in such games by ...
— One of the distinctive features in a wireless ad hoc network is lack of any central controller or single point of authority, in which each node/link then makes its own decision...
Chengnian Long, Qian Zhang, Bo Li, Huilong Yang, X...
This paper introduces a novel multiagent learning algorithm, Convergence with Model Learning and Safety (or CMLeS in short), which achieves convergence, targeted optimality agains...