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» Learning to Reason
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UAI
2008
13 years 9 months ago
Model-Based Bayesian Reinforcement Learning in Large Structured Domains
Model-based Bayesian reinforcement learning has generated significant interest in the AI community as it provides an elegant solution to the optimal exploration-exploitation trade...
Stéphane Ross, Joelle Pineau
CONNECTION
2006
101views more  CONNECTION 2006»
13 years 7 months ago
Learning acceptable windows of contingency
By learning a range of possible times over which the effect of an action can take place, a robot can reason more effectively about causal and contingent relationships in the world...
Kevin Gold, Brian Scassellati
AIR
2005
85views more  AIR 2005»
13 years 7 months ago
On Paradox of Fuzzy Modeling: Supervised Learning for Rectifying Fuzzy Membership Function
The paradox of fuzzy modeling is recognized due to the co-existence of its effectiveness of solving uncertain problems in the real world and the skepticism of its reasonability in ...
Shaopei Lin
CCIA
2005
Springer
14 years 1 months ago
Comparison of Strategies Based on Evolutionary Computation for the Design of Similarity Functions
One of the main keys in case-based reasoning system is the retrieval phase, where the most similar cases are retrieved by means of a similarity function. According to the problem, ...
Albert Fornells-Herrera, J. Camps Dausà, El...
EUROMICRO
2009
IEEE
14 years 2 months ago
Exercise Generation by Group Models for Autonomous Web-Based Learning
Abstract— Creating exercises for learners requires significant time. This is one reason, beside difficulties of discussing individualized tasks in a classroom setting, why often ...
Michael Sonntag