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ICML
2008
IEEE
14 years 8 months ago
Reinforcement learning with limited reinforcement: using Bayes risk for active learning in POMDPs
Partially Observable Markov Decision Processes (POMDPs) have succeeded in planning domains that require balancing actions that increase an agent's knowledge and actions that ...
Finale Doshi, Joelle Pineau, Nicholas Roy
AR
2008
118views more  AR 2008»
13 years 7 months ago
Efficient Behavior Learning Based on State Value Estimation of Self and Others
The existing reinforcement learning methods have been seriously suffering from the curse of dimension problem especially when they are applied to multiagent dynamic environments. ...
Yasutake Takahashi, Kentarou Noma, Minoru Asada
PERCOM
2009
ACM
14 years 8 months ago
Proactive and Adaptive Fuzzy Profile Control for Mobile Phones
In this paper we describe a context-sensitive way to change an active mobile phone profile. We present a method to create a proactive and adaptive phone profile control system that...
Miika Valtonen, Antti-Matti Vainio, Jukka Vanhala
ECAI
2010
Springer
13 years 8 months ago
Case-Based Multiagent Reinforcement Learning: Cases as Heuristics for Selection of Actions
This work presents a new approach that allows the use of cases in a case base as heuristics to speed up Multiagent Reinforcement Learning algorithms, combining Case-Based Reasoning...
Reinaldo A. C. Bianchi, Ramon López de M&aa...
IJCAI
2001
13 years 9 months ago
Exploiting Multiple Secondary Reinforcers in Policy Gradient Reinforcement Learning
Most formulations of Reinforcement Learning depend on a single reinforcement reward value to guide the search for the optimal policy solution. If observation of this reward is rar...
Gregory Z. Grudic, Lyle H. Ungar