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AUSAI
2003
Springer
15 years 12 months ago
Learning Action Selection Network of Intelligent Agent
Behavior-based artificial intelligent system is to derive the complicated behaviors by selecting appropriate one from a set of basic behaviors. Many robot systems have used behavi...
Eun-Kyung Yun, Sung-Bae Cho
COLT
2001
Springer
15 years 11 months ago
On Learning Monotone DNF under Product Distributions
We show that the class of monotone 2O( √ log n)-term DNF formulae can be PAC learned in polynomial time under the uniform distribution from random examples only. This is an expo...
Rocco A. Servedio
COLT
2008
Springer
15 years 8 months ago
Learning in the Limit with Adversarial Disturbances
We study distribution-dependent, data-dependent, learning in the limit with adversarial disturbance. We consider an optimization-based approach to learning binary classifiers from...
Constantine Caramanis, Shie Mannor
NIPS
2004
15 years 8 months ago
Brain Inspired Reinforcement Learning
Successful application of reinforcement learning algorithms often involves considerable hand-crafting of the necessary non-linear features to reduce the complexity of the value fu...
François Rivest, Yoshua Bengio, John Kalask...
ECAI
2010
Springer
15 years 7 months ago
Case-Based Multiagent Reinforcement Learning: Cases as Heuristics for Selection of Actions
This work presents a new approach that allows the use of cases in a case base as heuristics to speed up Multiagent Reinforcement Learning algorithms, combining Case-Based Reasoning...
Reinaldo A. C. Bianchi, Ramon López de M&aa...