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103
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ICML
1994
IEEE
15 years 3 months ago
Learning Without State-Estimation in Partially Observable Markovian Decision Processes
Reinforcement learning (RL) algorithms provide a sound theoretical basis for building learning control architectures for embedded agents. Unfortunately all of the theory and much ...
Satinder P. Singh, Tommi Jaakkola, Michael I. Jord...
97
Voted
SIGDIAL
2010
14 years 9 months ago
Investigating Clarification Strategies in a Hybrid POMDP Dialog Manager
We investigate the clarification strategies exhibited by a hybrid POMDP dialog manager based on data obtained from a phone-based user study. The dialog manager combines task struc...
Sebastian Varges, Silvia Quarteroni, Giuseppe Ricc...
CSL
2010
Springer
14 years 11 months ago
Bayesian update of dialogue state: A POMDP framework for spoken dialogue systems
This paper describes a statistically motivated framework for performing real-time dialogue state updates and policy learning in a spoken dialogue system. The framework is based on...
Blaise Thomson, Steve Young
ATAL
2008
Springer
15 years 1 months ago
Value-based observation compression for DEC-POMDPs
Representing agent policies compactly is essential for improving the scalability of multi-agent planning algorithms. In this paper, we focus on developing a pruning technique that...
Alan Carlin, Shlomo Zilberstein
IEEEPACT
2008
IEEE
15 years 6 months 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...