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NECO
2007
87views more  NECO 2007»
15 years 4 months ago
Reinforcement Learning State Estimator
cal networks in the learning of abstract and effector-specific representations of motor sequences. Neuroimage. 32, 714-727. (Neuroimage Editor’s Choice Award, 2006) Daw, N. D. Do...
Jun Morimoto, Kenji Doya
ICML
2002
IEEE
16 years 5 months ago
Action Refinement in Reinforcement Learning by Probability Smoothing
In many reinforcement learning applications, the set of possible actions can be partitioned by the programmer into subsets of similar actions. This paper presents a technique for ...
Carles Sierra, Dídac Busquets, Ramon L&oacu...
ICA
2010
Springer
15 years 5 months ago
Use of Prior Knowledge in a Non-Gaussian Method for Learning Linear Structural Equation Models
Abstract. We discuss causal structure learning based on linear structural equation models. Conventional learning methods most often assume Gaussianity and create many indistinguish...
Takanori Inazumi, Shohei Shimizu, Takashi Washio
JUCS
2010
159views more  JUCS 2010»
14 years 11 months ago
Authoring of Probabilistic Sequencing in Adaptive Hypermedia with Bayesian Networks
Abstract: One of the difficulties that self-directed learners face on their learning process is choosing the right learning resources. One of the goals of adaptive educational syst...
Sergio Gutiérrez Santos, Jaime Mayor-Berzal...
ALT
2009
Springer
16 years 1 months ago
Iterative Learning from Texts and Counterexamples Using Additional Information
Abstract. A variant of iterative learning in the limit (cf. [LZ96]) is studied when a learner gets negative examples refuting conjectures containing data in excess of the target la...
Sanjay Jain, Efim B. Kinber