Conversational recommender systems (CRSs) assist online users in their information-seeking and decision making tasks by supporting an interactive process. Although these processes...
We consider reinforcement learning as solving a Markov decision process with unknown transition distribution. Based on interaction with the environment, an estimate of the transit...
We develop an exact dynamic programming algorithm for partially observable stochastic games (POSGs). The algorithm is a synthesis of dynamic programming for partially observable M...
Eric A. Hansen, Daniel S. Bernstein, Shlomo Zilber...
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are a popular approach for modeling multi-agent systems acting in uncertain domains. Given the signi...
Pradeep Varakantham, Janusz Marecki, Yuichi Yabu, ...
A stochastic graph game is played by two players on a game graph with probabilistic transitions. We consider stochastic graph games with -regular winning conditions specified as Ra...