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» Using Learning in a Control Agent
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ML
2008
ACM
150views Machine Learning» more  ML 2008»
15 years 2 months ago
Learning probabilistic logic models from probabilistic examples
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
Jianzhong Chen, Stephen Muggleton, José Car...
103
Voted
ADMA
2006
Springer
110views Data Mining» more  ADMA 2006»
15 years 6 months ago
Learning with Local Drift Detection
Abstract. Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
João Gama, Gladys Castillo
139
Voted
ICML
1996
IEEE
16 years 3 months ago
Learning Evaluation Functions for Large Acyclic Domains
Some of the most successful recent applications of reinforcement learning have used neural networks and the TD algorithm to learn evaluation functions. In this paper, we examine t...
Justin A. Boyan, Andrew W. Moore
149
Voted
CSL
2007
Springer
15 years 2 months ago
Speaker-adaptive learning of resonance targets in a hidden trajectory model of speech coarticulation
A novel speaker-adaptive learning algorithm is developed and evaluated for a hidden trajectory model of speech coarticulation and reduction. Central to this model is the process o...
Dong Yu, Li Deng, Alex Acero
ICANNGA
2009
Springer
212views Algorithms» more  ICANNGA 2009»
15 years 9 months ago
Evolutionary Regression Modeling with Active Learning: An Application to Rainfall Runoff Modeling
Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alte...
Ivo Couckuyt, Dirk Gorissen, Hamed Rouhani, Eric L...