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ICML
2001
IEEE
16 years 7 months ago
Continuous-Time Hierarchical Reinforcement Learning
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
Mohammad Ghavamzadeh, Sridhar Mahadevan
ICCBR
2009
Springer
16 years 1 months ago
Case-Based Reasoning in Transfer Learning
Positive transfer learning (TL) occurs when, after gaining experience from learning how to solve a (source) task, the same learner can exploit this experience to improve performanc...
David W. Aha, Matthew Molineaux, Gita Sukthankar
EDUTAINMENT
2007
Springer
16 years 1 months ago
Method of Motion Data Processing Based on Manifold Learning
Due to the high-dimensionality of motion captured data which resulted in the complexity in motion analysis, a method of motion data processing based on manifold learning was propos...
Fengxia Li, Tianyu Huang, Lijie Li
ATAL
2005
Springer
16 years 13 days ago
Behavior transfer for value-function-based reinforcement learning
Temporal difference (TD) learning methods [22] have become popular reinforcement learning techniques in recent years. TD methods have had some experimental successes and have been...
Matthew E. Taylor, Peter Stone
ICML
2003
IEEE
16 years 4 days ago
The Significance of Temporal-Difference Learning in Self-Play Training TD-Rummy versus EVO-rummy
Reinforcement learning has been used for training game playing agents. The value function for a complex game must be approximated with a continuous function because the number of ...
Clifford Kotnik, Jugal K. Kalita