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» Learning to Reason
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UAI
2008
15 years 7 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»
15 years 6 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»
15 years 6 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
15 years 11 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
16 years 1 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