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UAI
2004
14 years 11 months ago
Dynamic Programming for Structured Continuous Markov Decision Problems
We describe an approach for exploiting structure in Markov Decision Processes with continuous state variables. At each step of the dynamic programming, the state space is dynamica...
Zhengzhu Feng, Richard Dearden, Nicolas Meuleau, R...
AAAI
2006
14 years 11 months ago
Compact, Convex Upper Bound Iteration for Approximate POMDP Planning
Partially observable Markov decision processes (POMDPs) are an intuitive and general way to model sequential decision making problems under uncertainty. Unfortunately, even approx...
Tao Wang, Pascal Poupart, Michael H. Bowling, Dale...
AAAI
2010
14 years 11 months ago
Relational Partially Observable MDPs
Relational Markov Decision Processes (MDP) are a useraction for stochastic planning problems since one can develop abstract solutions for them that are independent of domain size ...
Chenggang Wang, Roni Khardon
AAAI
2007
15 years 5 days ago
Scaling Up: Solving POMDPs through Value Based Clustering
Partially Observable Markov Decision Processes (POMDPs) provide an appropriately rich model for agents operating under partial knowledge of the environment. Since finding an opti...
Yan Virin, Guy Shani, Solomon Eyal Shimony, Ronen ...
ICTAI
2007
IEEE
15 years 4 months ago
Multi-criteria Decision Making for Local Coordination in Multi-agent Systems
Unlike mono-agent systems, multi-agent planing addresses the problem of resolving conflicts between individual and group interests. In this paper, we are using a Decentralized Ve...
Matthieu Boussard, Maroua Bouzid, Abdel-Illah Moua...