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» Algorithms for Inverse Reinforcement Learning
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JAIR
2008
148views more  JAIR 2008»
14 years 9 months ago
Learning Partially Observable Deterministic Action Models
We present exact algorithms for identifying deterministic-actions' effects and preconditions in dynamic partially observable domains. They apply when one does not know the ac...
Eyal Amir, Allen Chang
GECCO
2005
Springer
139views Optimization» more  GECCO 2005»
15 years 3 months ago
Event-driven learning classifier systems for online soccer games
This paper reports on the application of classifier systems to the acquisition of decision-making algorithms for agents in online soccer games. The objective of this research is t...
Yuji Sato, Ryutaro Kanno
IJON
2006
134views more  IJON 2006»
14 years 9 months ago
A new approach to fuzzy classifier systems and its application in self-generating neuro-fuzzy systems
A classifier system is a machine learning system that learns syntactically simple string rules (called classifiers) through a genetic algorithm to guide its performance in an arbi...
Mu-Chun Su, Chien-Hsing Chou, Eugene Lai, Jonathan...
SIGIR
2005
ACM
15 years 3 months ago
Using term informativeness for named entity detection
Informal communication (e-mail, bulletin boards) poses a difficult learning environment because traditional grammatical and lexical information are noisy. Other information is nec...
Jason D. M. Rennie, Tommi Jaakkola
IWCLS
2007
Springer
15 years 3 months ago
On Lookahead and Latent Learning in Simple LCS
Learning Classifier Systems use evolutionary algorithms to facilitate rule- discovery, where rule fitness is traditionally payoff based and assigned under a sharing scheme. Most c...
Larry Bull