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» Safe exploration for reinforcement learning
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IBERAMIA
2004
Springer
14 years 2 months ago
Mobile Robotic Supported Collaborative Learning (MRSCL)
In this paper we describe MRSCL Geometry a collaborative educational activity that explores the use of robotic technology and wirelessly connected Pocket PCs as tools for teaching ...
Rubén Mitnik, Miguel Nussbaum, Alvaro Soto
IDEAL
2004
Springer
14 years 2 months ago
Learning Users' Interests in a Market-Based Recommender System
Recommender systems are widely used to cope with the problem of information overload and, consequently, many recommendation methods have been developed. However, no one technique i...
Yan Zheng Wei, Luc Moreau, Nicholas R. Jennings
AOIS
2004
13 years 10 months ago
Market-Based Recommender Systems: Learning Users' Interests by Quality Classification
Recommender systems are widely used to cope with the problem of information overload and, consequently, many recommendation methods have been developed. However, no one technique i...
Yan Zheng Wei, Luc Moreau, Nicholas R. Jennings
GECCO
2005
Springer
162views Optimization» more  GECCO 2005»
14 years 2 months ago
An autonomous explore/exploit strategy
In reinforcement learning problems it has been considered that neither exploitation nor exploration can be pursued exclusively without failing at the task. The optimal balance bet...
Alex McMahon, Dan Scott, William N. L. Browne
ML
2002
ACM
133views Machine Learning» more  ML 2002»
13 years 8 months ago
Finite-time Analysis of the Multiarmed Bandit Problem
Reinforcement learning policies face the exploration versus exploitation dilemma, i.e. the search for a balance between exploring the environment to find profitable actions while t...
Peter Auer, Nicolò Cesa-Bianchi, Paul Fisch...