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IJCNN
2006
IEEE
15 years 11 months ago
Alleviating Catastrophic Forgetting via Multi-Objective Learning
— Handling catastrophic forgetting is an interesting and challenging topic in modeling the memory mechanisms of the human brain using machine learning models. From a more general...
Yaochu Jin, Bernhard Sendhoff
COLT
1998
Springer
15 years 9 months ago
Self Bounding Learning Algorithms
Most of the work which attempts to give bounds on the generalization error of the hypothesis generated by a learning algorithm is based on methods from the theory of uniform conve...
Yoav Freund
EWRL
2008
15 years 6 months ago
Policy Learning - A Unified Perspective with Applications in Robotics
Policy Learning approaches are among the best suited methods for high-dimensional, continuous control systems such as anthropomorphic robot arms and humanoid robots. In this paper,...
Jan Peters, Jens Kober, Duy Nguyen-Tuong
IJCAI
2007
15 years 6 months ago
Bayesian Inverse Reinforcement Learning
Inverse Reinforcement Learning (IRL) is the problem of learning the reward function underlying a Markov Decision Process given the dynamics of the system and the behaviour of an e...
Deepak Ramachandran, Eyal Amir
FLAIRS
2001
15 years 6 months ago
User-Agent Interactions in Mixed-Initiative Learning
Mixed-initiative learning integrates complementary human and automated reasoning, taking advantage of their respective reasoning styles and computational strengths in order to sol...
Dorin Marcu, Mihai Boicu, Gheorghe Tecuci