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» Reinforcement Learning with the Use of Costly Features
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EWCBR
2008
Springer
13 years 10 months ago
Recognizing the Enemy: Combining Reinforcement Learning with Strategy Selection Using Case-Based Reasoning
This paper presents CBRetaliate, an agent that combines Case-Based Reasoning (CBR) and Reinforcement Learning (RL) algorithms. Unlike most previous work where RL is used to improve...
Bryan Auslander, Stephen Lee-Urban, Chad Hogg, H&e...
FLAIRS
2004
13 years 10 months ago
Developing Task Specific Sensing Strategies Using Reinforcement Learning
Robots that can adapt and perform multiple tasks promise to be a powerful tool with many applications. In order to achieve such robots, control systems have to be constructed that...
Srividhya Rajendran, Manfred Huber
ICML
2006
IEEE
14 years 9 months ago
PAC model-free reinforcement learning
For a Markov Decision Process with finite state (size S) and action spaces (size A per state), we propose a new algorithm--Delayed Q-Learning. We prove it is PAC, achieving near o...
Alexander L. Strehl, Lihong Li, Eric Wiewiora, Joh...
ICADL
2007
Springer
147views Education» more  ICADL 2007»
14 years 3 months ago
Feature Reinforcement Approach to Poly-lingual Text Categorization
With the rapid emergence and proliferation of Internet and the trend of globalization, a tremendous amount of textual documents written in different languages are electronically ac...
Chih-Ping Wei, Huihua Shi, Christopher C. Yang
ICDCSW
2006
IEEE
14 years 3 months ago
Improve Searching by Reinforcement Learning in Unstructured P2Ps
— Existing searching schemes in unstructured P2Ps can be categorized as either blind or informed. The quality of query results in blind schemes is low. Informed schemes use simpl...
Xiuqi Li, Jie Wu