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NIPS
2001
13 years 8 months ago
Predictive Representations of State
We show that states of a dynamical system can be usefully represented by multi-step, action-conditional predictions of future observations. State representations that are grounded...
Michael L. Littman, Richard S. Sutton, Satinder P....
JSAC
2011
82views more  JSAC 2011»
13 years 2 months ago
Optimal Cognitive Access of Markovian Channels under Tight Collision Constraints
Abstract—The problem of cognitive access of channels of primary users by a secondary user is considered. The transmissions of primary users are modeled as independent continuous-...
Xin Li, Qianchuan Zhao, Xiaohong Guan, Lang Tong
AAAI
2004
13 years 9 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
ICML
2008
IEEE
14 years 8 months ago
Reinforcement learning with limited reinforcement: using Bayes risk for active learning in POMDPs
Partially Observable Markov Decision Processes (POMDPs) have succeeded in planning domains that require balancing actions that increase an agent's knowledge and actions that ...
Finale Doshi, Joelle Pineau, Nicholas Roy
AAAI
2010
13 years 9 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