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143
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AAAI
2012
13 years 4 months ago
Kernel-Based Reinforcement Learning on Representative States
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
Branislav Kveton, Georgios Theocharous
106
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AI
2006
Springer
15 years 5 months ago
An Efficient Resource Allocation Approach in Real-Time Stochastic Environment
We are interested in contributing to solving effectively a particular type of real-time stochastic resource allocation problem. Firstly, one distinction is that certain tasks may c...
Pierrick Plamondon, Brahim Chaib-draa, Abder Rezak...
147
Voted
ACL
2010
14 years 12 months ago
Towards Relational POMDPs for Adaptive Dialogue Management
Open-ended spoken interactions are typically characterised by both structural complexity and high levels of uncertainty, making dialogue management in such settings a particularly...
Pierre Lison
HICSS
2005
IEEE
139views Biometrics» more  HICSS 2005»
15 years 7 months ago
Complex Decision Making Processes: their Modelling and Support
Decision making processes and systems to support the same have focused for the most part on narrow disciplines, paradigms, perspectives, and pre-determined processes. Apart from t...
Angela Liew, David Sundaram
JAIR
2008
145views more  JAIR 2008»
15 years 1 months ago
Communication-Based Decomposition Mechanisms for Decentralized MDPs
Multi-agent planning in stochastic environments can be framed formally as a decentralized Markov decision problem. Many real-life distributed problems that arise in manufacturing,...
Claudia V. Goldman, Shlomo Zilberstein