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JAIR
2000
152views more  JAIR 2000»
15 years 1 months ago
Value-Function Approximations for Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
Milos Hauskrecht
ICDM
2010
IEEE
127views Data Mining» more  ICDM 2010»
14 years 11 months ago
Learning Markov Network Structure with Decision Trees
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Daniel Lowd, Jesse Davis
CVIU
2010
163views more  CVIU 2010»
15 years 1 months ago
Automated handwashing assistance for persons with dementia using video and a partially observable Markov decision process
This paper presents a real-time vision-based system to assist a person with dementia wash their hands. The system uses only video inputs, and assistance is given as either verbal ...
Jesse Hoey, Pascal Poupart, Axel von Bertoldi, Tam...
QEST
2008
IEEE
15 years 7 months ago
Symbolic Magnifying Lens Abstraction in Markov Decision Processes
Magnifying Lens Abstraction in Markov Decision Processes ∗ Pritam Roy1 David Parker2 Gethin Norman2 Luca de Alfaro1 Computer Engineering Dept, UC Santa Cruz, Santa Cruz, CA, USA ...
Pritam Roy, David Parker, Gethin Norman, Luca de A...
IJCAI
2007
15 years 2 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup