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AAAI
1997
14 years 11 months ago
Model Minimization in Markov Decision Processes
Many stochastic planning problems can be represented using Markov Decision Processes (MDPs). A difficulty with using these MDP representations is that the common algorithms for so...
Thomas Dean, Robert Givan
EMMCVPR
2001
Springer
15 years 2 months ago
A Hierarchical Markov Random Field Model for Figure-Ground Segregation
To segregate overlapping objects into depth layers requires the integration of local occlusion cues distributed over the entire image into a global percept. We propose to model thi...
Stella X. Yu, Tai Sing Lee, Takeo Kanade
AAAI
1996
14 years 11 months ago
Computing Optimal Policies for Partially Observable Decision Processes Using Compact Representations
: Partially-observable Markov decision processes provide a very general model for decision-theoretic planning problems, allowing the trade-offs between various courses of actions t...
Craig Boutilier, David Poole
GLOBECOM
2010
IEEE
14 years 7 months ago
Cooperative Relay Scheduling under Partial State Information in Energy Harvesting Sensor Networks
Abstract--Sensors equipped with energy harvesting and cooperative communication capabilities are a viable solution to the power limitations of Wireless Sensor Networks (WSNs) assoc...
Huijiang Li, Neeraj Jaggi, Biplab Sikdar
ICTAI
1996
IEEE
15 years 2 months ago
Incremental Markov-Model Planning
This paper presents an approach to building plans using partially observable Markov decision processes. The approach begins with a base solution that assumes full observability. T...
Richard Washington