The field of multiagent decision making is extending its tools from classical game theory by embracing reinforcement learning, statistical analysis, and opponent modeling. For ex...
Michael Wunder, Michael Kaisers, John Robert Yaros...
Distributed Partially Observable Markov Decision Problems (DisPOMDPs) are emerging as a popular approach for modeling sequential decision making in teams operating under uncertain...
We develop a model of normative systems in which agents are assumed to have multiple goals of increasing priority, and investigate the computational complexity and game theoretic ...
We introduce a new class of games, congestion games with failures (CGFs), which extends the class of congestion games to allow for facility failures. In a basic CGF (BCGF) agents ...
We propose a general framework for multi-context reasoning which allows us to combine arbitrary monotonic and nonmonotonic logics. Nonmonotonic bridge rules are used to specify th...