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FLAIRS
2006
13 years 9 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
IJCAI
2001
13 years 9 months ago
Symbolic Dynamic Programming for First-Order MDPs
We present a dynamic programming approach for the solution of first-order Markov decisions processes. This technique uses an MDP whose dynamics is represented in a variant of the ...
Craig Boutilier, Raymond Reiter, Bob Price
ML
2002
ACM
121views Machine Learning» more  ML 2002»
13 years 7 months ago
Near-Optimal Reinforcement Learning in Polynomial Time
We present new algorithms for reinforcement learning, and prove that they have polynomial bounds on the resources required to achieve near-optimal return in general Markov decisio...
Michael J. Kearns, Satinder P. Singh
ICMLA
2009
13 years 5 months ago
Automatic Feature Selection for Model-Based Reinforcement Learning in Factored MDPs
Abstract--Feature selection is an important challenge in machine learning. Unfortunately, most methods for automating feature selection are designed for supervised learning tasks a...
Mark Kroon, Shimon Whiteson
AIPS
2003
13 years 9 months ago
Recommendation as a Stochastic Sequential Decision Problem
Recommender systems — systems that suggest to users in e-commerce sites items that might interest them — adopt a static view of the recommendation process and treat it as a pr...
Ronen I. Brafman, David Heckerman, Guy Shani