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UAI
2008
13 years 7 months ago
Model-Based Bayesian Reinforcement Learning in Large Structured Domains
Model-based Bayesian reinforcement learning has generated significant interest in the AI community as it provides an elegant solution to the optimal exploration-exploitation trade...
Stéphane Ross, Joelle Pineau
EACL
2006
ACL Anthology
13 years 7 months ago
Using Reinforcement Learning to Build a Better Model of Dialogue State
Given the growing complexity of tasks that spoken dialogue systems are trying to handle, Reinforcement Learning (RL) has been increasingly used as a way of automatically learning ...
Joel R. Tetreault, Diane J. Litman
ICRA
2006
IEEE
131views Robotics» more  ICRA 2006»
14 years 6 days ago
Using Reinforcement Learning to Improve Exploration Trajectories for Error Minimization
Abstract— The mapping and localization problems have received considerable attention in robotics recently. The exploration problem that drives mapping has started to generate sim...
Thomas Kollar, Nicholas Roy
ICCD
2003
IEEE
111views Hardware» more  ICCD 2003»
14 years 3 months ago
Reducing Operand Transport Complexity of Superscalar Processors using Distributed Register Files
A critical problem in wide-issue superscalar processors is the limit on cycle time imposed by the central register file and operand bypass network. In this paper, a distributed re...
Santithorn Bunchua, D. Scott Wills, Linda M. Wills
IEEEPACT
2008
IEEE
14 years 17 days ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...