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IJCAI
2001
13 years 9 months ago
Using Case-Base Data to Learn Adaptation Knowledge for Design
One advantage of Case-Based Reasoning (CBR) is the relative ease of constructing and maintaining CBR systems, especially as a number of commercial CBR tools are available. However...
Jacek Jarmulak, Susan Craw, Ray Rowe
ACL
2012
11 years 10 months ago
Learning High-Level Planning from Text
Comprehending action preconditions and effects is an essential step in modeling the dynamics of the world. In this paper, we express the semantics of precondition relations extrac...
S. R. K. Branavan, Nate Kushman, Tao Lei, Regina B...
COLING
1992
13 years 9 months ago
Syntactic Ambiguity Resolution Using A Discrimination and Robustness Oriented Adaptive Learning Algorithm
In this paper, a discrimination and robusmess oriented adaptive learning procedure is proposed to deal with the task of syntactic ambiguity resolution. Owing to the problem of ins...
Tung-Hui Chiang, Yi-Chung Lin, Keh-Yih Su
CDC
2010
IEEE
160views Control Systems» more  CDC 2010»
13 years 2 months ago
Adaptive bases for Q-learning
Abstract-- We consider reinforcement learning, and in particular, the Q-learning algorithm in large state and action spaces. In order to cope with the size of the spaces, a functio...
Dotan Di Castro, Shie Mannor
GECCO
2005
Springer
153views Optimization» more  GECCO 2005»
14 years 1 months ago
Evolving neural network ensembles for control problems
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
David Pardoe, Michael S. Ryoo, Risto Miikkulainen