Optimally Solving Dec-POMDPs as Continuous-State MDPs
From MaRDI portal
Publication:2790147
DOI10.1613/jair.4623zbMath1352.68220OpenAlexW309675244MaRDI QIDQ2790147
Jilles Steeve Dibangoye, Christopher Amato, François Charpillet, Olivier Buffet
Publication date: 3 March 2016
Published in: Journal of Artificial Intelligence Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1613/jair.4623
Markov and semi-Markov decision processes (90C40) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20) Agent technology and artificial intelligence (68T42)
Related Items (7)
Knowledge-based strategies for multi-agent teams playing against nature ⋮ Rethinking formal models of partially observable multiagent decision making ⋮ Value functions for depth-limited solving in zero-sum imperfect-information games ⋮ Solving zero-sum one-sided partially observable stochastic games ⋮ Unnamed Item ⋮ Multi-agent reinforcement learning algorithm to solve a partially-observable multi-agent problem in disaster response ⋮ Multi-agent reinforcement learning: a selective overview of theories and algorithms
This page was built for publication: Optimally Solving Dec-POMDPs as Continuous-State MDPs
