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» Using model knowledge for learning inverse dynamics
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ITS
2004
Springer
105views Multimedia» more  ITS 2004»
15 years 8 months ago
The Massive User Modelling System (MUMS)
Developing a learner model containing an accurate representation of a learner’s knowledge is made more difficult in distributed learning environments where the learner uses mult...
Christopher A. Brooks, Mike Winter, Jim E. Greer, ...
120
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NN
1998
Springer
102views Neural Networks» more  NN 1998»
15 years 2 months ago
A learning model for oscillatory networks
A learning model for coupled oscillators is proposed. The proposed learning rule takes a simple form by which the intrinsic frequencies of the component oscillators and the coupli...
Jun Nishii
129
Voted
ICML
2007
IEEE
16 years 3 months ago
Tracking value function dynamics to improve reinforcement learning with piecewise linear function approximation
Reinforcement learning algorithms can become unstable when combined with linear function approximation. Algorithms that minimize the mean-square Bellman error are guaranteed to co...
Chee Wee Phua, Robert Fitch
AGI
2008
15 years 4 months ago
Artificial General Intelligence through Large-Scale, Multimodal Bayesian Learning
Abstract. An artificial system that achieves human-level performance on opendomain tasks must have a huge amount of knowledge about the world. We argue that the most feasible way t...
Brian Milch
106
Voted
DSS
2007
120views more  DSS 2007»
15 years 2 months ago
Could the use of a knowledge-based system lead to implicit learning?
The primary objective of a knowledge-based system (KBS) is to use stored knowledge to provide support for decision-making activities. Empirical studies identify improvements in de...
Solomon R. Antony, Radhika Santhanam