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» Abstracting Reusable Cases from Reinforcement Learning
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TAOSD
2010
13 years 4 days ago
Aspect-Oriented Design with Reusable Aspect Models
The idea behind Aspect-Oriented Modeling (AOM) is to apply aspect-oriented techniques to (software) models with the aim of modularizing crosscutting concerns. This can be done with...
Jörg Kienzle, Wisam Al Abed, Franck Fleurey, ...
ICCBR
2009
Springer
13 years 12 months ago
Improving Reinforcement Learning by Using Case Based Heuristics
This work presents a new approach that allows the use of cases in a case base as heuristics to speed up Reinforcement Learning algorithms, combining Case Based Reasoning (CBR) and ...
Reinaldo A. C. Bianchi, Raquel Ros, Ramon Ló...
IDEAL
2007
Springer
13 years 11 months ago
Skill Combination for Reinforcement Learning
Recently researchers have introduced methods to develop reusable knowledge in reinforcement learning (RL). In this paper, we define simple principles to combine skills in reinforce...
Zhihui Luo, David A. Bell, Barry McCollum
NIPS
1993
13 years 6 months ago
Robust Reinforcement Learning in Motion Planning
While exploring to nd better solutions, an agent performing online reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, ...
Satinder P. Singh, Andrew G. Barto, Roderic A. Gru...
ECML
2004
Springer
13 years 10 months ago
Batch Reinforcement Learning with State Importance
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
Lihong Li, Vadim Bulitko, Russell Greiner