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ICML
2006
IEEE
14 years 1 months ago
Automatic basis function construction for approximate dynamic programming and reinforcement learning
We address the problem of automatically constructing basis functions for linear approximation of the value function of a Markov Decision Process (MDP). Our work builds on results ...
Philipp W. Keller, Shie Mannor, Doina Precup
VL
2000
IEEE
14 years 6 days ago
Learning and Reuse of a Visual Programming Language
Five science teachers were observed during two selfstudy sessions where they learned to use Visual AgenTalk (VAT). In the first session they learned basic skills; in the second, t...
Mary Beth Rosson, Cheryl D. Seals
GECCO
2003
Springer
128views Optimization» more  GECCO 2003»
14 years 1 months ago
Learning Biped Locomotion from First Principles on a Simulated Humanoid Robot Using Linear Genetic Programming
We describe the first instance of an approach for control programming of humanoid robots, based on evolution as the main adaptation mechanism. In an attempt to overcome some of th...
Krister Wolff, Peter Nordin
ETS
2002
IEEE
144views Hardware» more  ETS 2002»
13 years 7 months ago
Best Practices in Technology-Mediated Learning in American Business Education
Many business schools are re-examining management education, and many view advanced information technology as an enabler of innovative and effective learning. How best to approach...
Gretchen Gemeinhardt
ICDM
2005
IEEE
116views Data Mining» more  ICDM 2005»
14 years 1 months ago
Learning Functional Dependency Networks Based on Genetic Programming
Bayesian Network (BN) is a powerful network model, which represents a set of variables in the domain and provides the probabilistic relationships among them. But BN can handle dis...
Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong