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» Using reinforcement learning to adapt an imitation task
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NIPS
2008
13 years 9 months ago
Bayesian Kernel Shaping for Learning Control
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
Jo-Anne Ting, Mrinal Kalakrishnan, Sethu Vijayakum...
ATAL
2008
Springer
13 years 9 months ago
Artificial agents learning human fairness
Recent advances in technology allow multi-agent systems to be deployed in cooperation with or as a service for humans. Typically, those systems are designed assuming individually ...
Steven de Jong, Karl Tuyls, Katja Verbeeck
IJCSA
2008
96views more  IJCSA 2008»
13 years 7 months ago
Integration of Educational Specifications and Standards to Support Adaptive Learning Scenarios in ADAPTAPlan
ADAPTAPlan project provides dynamic assistance for reducing authors' effort in developing instructional design tasks using user modelling, planning and machine learning techn...
Silvia Baldiris, Olga C. Santos, Carmen Barrera, J...
AAAI
2010
13 years 9 months ago
Towards Multiagent Meta-level Control
Embedded systems consisting of collaborating agents capable of interacting with their environment are becoming ubiquitous. It is crucial for these systems to be able to adapt to t...
Shanjun Cheng, Anita Raja, Victor R. Lesser
CI
2005
106views more  CI 2005»
13 years 7 months ago
Incremental Learning of Procedural Planning Knowledge in Challenging Environments
Autonomous agents that learn about their environment can be divided into two broad classes. One class of existing learners, reinforcement learners, typically employ weak learning ...
Douglas J. Pearson, John E. Laird