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AAAI
2006
15 years 8 months ago
Hard Constrained Semi-Markov Decision Processes
In multiple criteria Markov Decision Processes (MDP) where multiple costs are incurred at every decision point, current methods solve them by minimising the expected primary cost ...
Wai-Leong Yeow, Chen-Khong Tham, Wai-Choong Wong
AAAI
1998
15 years 8 months ago
Solving Very Large Weakly Coupled Markov Decision Processes
We present a technique for computing approximately optimal solutions to stochastic resource allocation problems modeled as Markov decision processes (MDPs). We exploit two key pro...
Nicolas Meuleau, Milos Hauskrecht, Kee-Eung Kim, L...
ECAI
2010
Springer
15 years 7 months ago
On Finding Compromise Solutions in Multiobjective Markov Decision Processes
A Markov Decision Process (MDP) is a general model for solving planning problems under uncertainty. It has been extended to multiobjective MDP to address multicriteria or multiagen...
Patrice Perny, Paul Weng
CORR
2010
Springer
154views Education» more  CORR 2010»
15 years 6 months ago
Causal Markov condition for submodular information measures
The causal Markov condition (CMC) is a postulate that links observations to causality. It describes the conditional independences among the observations that are entailed by a cau...
Bastian Steudel, Dominik Janzing, Bernhard Sch&oum...
ICIP
2010
IEEE
15 years 4 months ago
Detecting pitching frames in baseball game video using Markov random walk
Pitching is the starting point of an event in baseball games. Hence, locating pitching shots is a critical step in content analysis of a baseball game video. However, pitching fra...
Chih-Yi Chiu, Po-Chih Lin, Wei-Ming Chang, Hsin-Mi...