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» Finding Structure in Reinforcement Learning
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AAAI
2000
15 years 4 months ago
Information Extraction with HMM Structures Learned by Stochastic Optimization
Recent research has demonstrated the strong performance of hidden Markov models applied to information extraction--the task of populating database slots with corresponding phrases...
Dayne Freitag, Andrew McCallum
132
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HEURISTICS
2008
170views more  HEURISTICS 2008»
15 years 3 months ago
Accelerating autonomous learning by using heuristic selection of actions
This paper investigates how to make improved action selection for online policy learning in robotic scenarios using reinforcement learning (RL) algorithms. Since finding control po...
Reinaldo A. C. Bianchi, Carlos H. C. Ribeiro, Anna...
CORR
2002
Springer
100views Education» more  CORR 2002»
15 years 3 months ago
A neural model for multi-expert architectures
We present a generalization of conventional artificial neural networks that allows for a functional equivalence to multi-expert systems. The new model provides an architectural fr...
Marc Toussaint
123
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JMLR
2010
113views more  JMLR 2010»
14 years 10 months ago
Optimal Search on Clustered Structural Constraint for Learning Bayesian Network Structure
We study the problem of learning an optimal Bayesian network in a constrained search space; skeletons are compelled to be subgraphs of a given undirected graph called the super-st...
Kaname Kojima, Eric Perrier, Seiya Imoto, Satoru M...
GECCO
2006
Springer
195views Optimization» more  GECCO 2006»
15 years 7 months ago
Studying XCS/BOA learning in Boolean functions: structure encoding and random Boolean functions
Recently, studies with the XCS classifier system on Boolean functions have shown that in certain types of functions simple crossover operators can lead to disruption and, conseque...
Martin V. Butz, Martin Pelikan