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131
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HRI
2007
ACM
15 years 6 months ago
Learning by demonstration with critique from a human teacher
Learning by demonstration can be a powerful and natural tool for developing robot control policies. That is, instead of tedious hand-coding, a robot may learn a control policy by ...
Brenna Argall, Brett Browning, Manuela M. Veloso
130
Voted
CEC
2010
IEEE
15 years 3 months ago
Adaptive learning particle swarm optimizer-II for global optimization
This paper presents an updated version of the adaptive learning particle swarm optimizer (ALPSO) [6], we call it ALPSO-II. In order to improve the performance of ALPSO on multi-mod...
Changhe Li, Shengxiang Yang
122
Voted
ACL
2011
14 years 6 months ago
Learning to Win by Reading Manuals in a Monte-Carlo Framework
This paper presents a novel approach for leveraging automatically extracted textual knowledge to improve the performance of control applications such as games. Our ultimate goal i...
S. R. K. Branavan, David Silver, Regina Barzilay
113
Voted
EWCBR
2008
Springer
15 years 4 months ago
Knowledge Planning and Learned Personalization for Web-Based Case Adaptation
How to endow case-based reasoning systems with effective case adaptation capabilities is a classic problem. A significant impediment to developing automated adaptation procedures i...
David B. Leake, Jay H. Powell
157
Voted
IEEECIT
2010
IEEE
15 years 21 days ago
Learning Autonomic Security Reconfiguration Policies
Abstract--We explore the idea of applying machine learning techniques to automatically infer risk-adaptive policies to reconfigure a network security architecture when the context ...
Juan E. Tapiador, John A. Clark