Abstract. An optimal probabilistic-planning algorithm solves a problem, usually modeled by a Markov decision process, by finding its optimal policy. In this paper, we study the k ...
The growing diffusion of portable devices enables users to benefit from anytime and anywhere impromptu collaboration. Appropriate policy models that take into account the dynamici...
Abstract— This paper introduces a novel architecture for performing the core computations required by dynamic programming (DP) techniques. The latter pertain to a vast range of a...
Decentralized decision making under uncertainty has been shown to be intractable when each agent has different partial information about the domain. Thus, improving the applicabil...
Partially observable stochastic games (POSGs) provide a rich mathematical framework for planning under uncertainty by a group of agents. However, this modeling advantage comes wit...