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» Efficient Approximation of Optimal Control for Markov Games
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UAI
1998
14 years 10 months ago
Flexible Decomposition Algorithms for Weakly Coupled Markov Decision Problems
This paper presents two new approaches to decomposing and solving large Markov decision problems (MDPs), a partial decoupling method and a complete decoupling method. In these app...
Ronald Parr
UAI
2008
14 years 11 months ago
Partitioned Linear Programming Approximations for MDPs
Approximate linear programming (ALP) is an efficient approach to solving large factored Markov decision processes (MDPs). The main idea of the method is to approximate the optimal...
Branislav Kveton, Milos Hauskrecht
AAAI
2006
14 years 11 months ago
Learning Basis Functions in Hybrid Domains
Markov decision processes (MDPs) with discrete and continuous state and action components can be solved efficiently by hybrid approximate linear programming (HALP). The main idea ...
Branislav Kveton, Milos Hauskrecht
ICCAD
1999
IEEE
101views Hardware» more  ICCAD 1999»
15 years 1 months ago
Efficient model reduction of interconnect via approximate system gramians
Krylov-subspace based methods for generating low-order models of complicated interconnect are extremely effective, but there is no optimality theory for the resulting models. Alte...
Jing-Rebecca Li, Jacob White
PAMI
2007
186views more  PAMI 2007»
14 years 9 months ago
Value-Directed Human Behavior Analysis from Video Using Partially Observable Markov Decision Processes
—This paper presents a method for learning decision theoretic models of human behaviors from video data. Our system learns relationships between the movements of a person, the co...
Jesse Hoey, James J. Little