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» Markov Decision Processes with Arbitrary Reward Processes
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NIPS
2000
15 years 5 months ago
APRICODD: Approximate Policy Construction Using Decision Diagrams
We propose a method of approximate dynamic programming for Markov decision processes (MDPs) using algebraic decision diagrams (ADDs). We produce near-optimal value functions and p...
Robert St-Aubin, Jesse Hoey, Craig Boutilier
AAAI
2010
15 years 5 months ago
Representation Discovery in Sequential Decision Making
Automatically constructing novel representations of tasks from analysis of state spaces is a longstanding fundamental challenge in AI. I review recent progress on this problem for...
Sridhar Mahadevan
JIRS
2000
121views more  JIRS 2000»
15 years 3 months ago
Entropy-Based Markov Chains for Multisensor Fusion
Abstract. This paper proposes an entropy based Markov chain (EMC) fusion technique and demonstrates its applications in multisensor fusion. Self-entropy and conditional entropy, wh...
Albert C. S. Chung, Helen C. Shen
ICASSP
2011
IEEE
14 years 7 months ago
A modified MAP criterion based on hidden Markov model for voice activity detecion
The maximum a posteriori (MAP) criterion is broadly used in the statistical model-based voice activity detection (VAD) approaches. In the conventional MAP criterion, however, the ...
Shiwen Deng, Jiqing Han, Tieran Zheng, Guibin Zhen...
ICML
2004
IEEE
16 years 4 months ago
Learning low dimensional predictive representations
Predictive state representations (PSRs) have recently been proposed as an alternative to partially observable Markov decision processes (POMDPs) for representing the state of a dy...
Matthew Rosencrantz, Geoffrey J. Gordon, Sebastian...