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» Planning with predictive state representations
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JIRS
2000
144views more  JIRS 2000»
15 years 1 months ago
An Integrated Approach of Learning, Planning, and Execution
Agents (hardware or software) that act autonomously in an environment have to be able to integrate three basic behaviors: planning, execution, and learning. This integration is man...
Ramón García-Martínez, Daniel...
AAAI
1997
15 years 2 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
ISRR
2005
Springer
154views Robotics» more  ISRR 2005»
15 years 7 months ago
Session Overview Planning
ys when planning meant searching for a sequence of abstract actions that satisfied some symbolic predicate. Robots can now learn their own representations through statistical infe...
Nicholas Roy, Roland Siegwart
NIPS
1997
15 years 2 months ago
Generalized Prioritized Sweeping
Prioritized sweeping is a model-based reinforcement learning method that attempts to focus an agent’s limited computational resources to achieve a good estimate of the value of ...
David Andre, Nir Friedman, Ronald Parr
151
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SDM
2012
SIAM
278views Data Mining» more  SDM 2012»
13 years 3 months ago
Legislative Prediction via Random Walks over a Heterogeneous Graph
In this article, we propose a random walk-based model to predict legislators’ votes on a set of bills. In particular, we first convert roll call data, i.e. the recorded votes a...
Jun Wang, Kush R. Varshney, Aleksandra Mojsilovic