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ICML
2006
IEEE
15 years 10 months ago
Automatic basis function construction for approximate dynamic programming and reinforcement learning
We address the problem of automatically constructing basis functions for linear approximation of the value function of a Markov Decision Process (MDP). Our work builds on results ...
Philipp W. Keller, Shie Mannor, Doina Precup
ECBS
2009
IEEE
113views Hardware» more  ECBS 2009»
15 years 10 months ago
Modeling and Analysis of Probabilistic Timed Systems
Probabilistic models are useful for analyzing systems which operate under the presence of uncertainty. In this paper, we present a technique for verifying safety and liveness prop...
Abhishek Dubey, Derek Riley, Sherif Abdelwahed, Te...
AAAI
2008
15 years 6 months ago
Interaction Structure and Dimensionality Reduction in Decentralized MDPs
Decentralized Markov Decision Processes are a powerful general model of decentralized, cooperative multi-agent problem solving. The high complexity of the general problem leads to...
Martin Allen, Marek Petrik, Shlomo Zilberstein
153
Voted
JMLR
2006
190views more  JMLR 2006»
15 years 3 months ago
Causal Graph Based Decomposition of Factored MDPs
We present Variable Influence Structure Analysis, or VISA, an algorithm that performs hierarchical decomposition of factored Markov decision processes. VISA uses a dynamic Bayesia...
Anders Jonsson, Andrew G. Barto
IJCNLP
2005
Springer
15 years 9 months ago
Automatic Partial Parsing Rule Acquisition Using Decision Tree Induction
Abstract. Partial parsing techniques try to recover syntactic information efficiently and reliably by sacrificing completeness and depth of analysis. One of the difficulties of pa...
Myung-Seok Choi, Chul Su Lim, Key-Sun Choi