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ICML
2002
IEEE
16 years 5 months ago
Reinforcement Learning and Shaping: Encouraging Intended Behaviors
We explore dynamic shaping to integrate our prior beliefs of the final policy into a conventional reinforcement learning system. Shaping provides a positive or negative artificial...
Adam Laud, Gerald DeJong
IJCAI
2001
15 years 5 months ago
R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
Ronen I. Brafman, Moshe Tennenholtz
ATAL
2007
Springer
15 years 10 months ago
Transfer via inter-task mappings in policy search reinforcement learning
The ambitious goal of transfer learning is to accelerate learning on a target task after training on a different, but related, source task. While many past transfer methods have f...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
IUI
1998
ACM
15 years 8 months ago
Task-sensitive Cinematography Interfaces for Interactive 3D Learning Environments
Interactive3Dlearningenvironmentscanproviderichproblemsolving experiences with unparalleled visual impact. In these environments, students interactively solve problems by directin...
William H. Bares, Luke S. Zettlemoyer, Dennis W. R...
CVPR
2012
IEEE
13 years 6 months ago
Submodular dictionary learning for sparse coding
A greedy-based approach to learn a compact and discriminative dictionary for sparse representation is presented. We propose an objective function consisting of two components: ent...
Zhuolin Jiang, Guangxiao Zhang, Larry S. Davis