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JCP
2007
143views more  JCP 2007»
13 years 7 months ago
Noisy K Best-Paths for Approximate Dynamic Programming with Application to Portfolio Optimization
Abstract— We describe a general method to transform a non-Markovian sequential decision problem into a supervised learning problem using a K-bestpaths algorithm. We consider an a...
Nicolas Chapados, Yoshua Bengio
NIPS
1993
13 years 8 months ago
Using Local Trajectory Optimizers to Speed Up Global Optimization in Dynamic Programming
Dynamic programming provides a methodology to develop planners and controllers for nonlinear systems. However, general dynamic programming is computationally intractable. We have ...
Christopher G. Atkeson
CHI
2001
ACM
14 years 7 months ago
Locus of feedback control in computer-based tutoring: impact on learning rate, achievement and attitudes
The advent of second-generation intelligent computer tutors raises an important instructional design question: when should tutorial advice be presented in problem solving? This pa...
Albert T. Corbett, John R. Anderson
AIED
2009
Springer
14 years 1 months ago
Scaffolding Motivation and Metacognition in Learning Programming
This paper explores the role that feedback based on past actions and motivational states of the learner can have in a motivationally and metacognitively aware Intelligent Tutoring ...
Alison Hull, Benedict du Boulay
ICML
1996
IEEE
13 years 11 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos