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AAAI
2010
13 years 11 months ago
Compressing POMDPs Using Locality Preserving Non-Negative Matrix Factorization
Partially Observable Markov Decision Processes (POMDPs) are a well-established and rigorous framework for sequential decision-making under uncertainty. POMDPs are well-known to be...
Georgios Theocharous, Sridhar Mahadevan
ICMLA
2008
13 years 11 months ago
Prediction-Directed Compression of POMDPs
High dimensionality of belief space in Partially Observable Markov Decision Processes (POMDPs) is one of the major causes that severely restricts the applicability of this model. ...
Abdeslam Boularias, Masoumeh T. Izadi, Brahim Chai...
IJCAI
2007
13 years 11 months ago
First Order Decision Diagrams for Relational MDPs
Dynamic programming algorithms provide a basic tool identifying optimal solutions in Markov Decision Processes (MDP). The paper develops a representation for decision diagrams sui...
Chenggang Wang, Saket Joshi, Roni Khardon
AAAI
2004
13 years 11 months ago
Stochastic Local Search for POMDP Controllers
The search for finite-state controllers for partially observable Markov decision processes (POMDPs) is often based on approaches like gradient ascent, attractive because of their ...
Darius Braziunas, Craig Boutilier
FLAIRS
2006
13 years 11 months ago
Stochastic Deliberation Scheduling using GSMDPs
We propose a new decision-theoretic approach for solving execution-time deliberation scheduling problems using recent advances in Generalized Semi-Markov Decision Processes (GSMDP...
Kurt D. Krebsbach