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ECML
2005
Springer
16 years 12 days ago
Using Advice to Transfer Knowledge Acquired in One Reinforcement Learning Task to Another
We present a method for transferring knowledge learned in one task to a related task. Our problem solvers employ reinforcement learning to acquire a model for one task. We then tra...
Lisa Torrey, Trevor Walker, Jude W. Shavlik, Richa...
NIPS
2007
15 years 8 months ago
Multiple-Instance Active Learning
We present a framework for active learning in the multiple-instance (MI) setting. In an MI learning problem, instances are naturally organized into bags and it is the bags, instea...
Burr Settles, Mark Craven, Soumya Ray
CE
2006
161views more  CE 2006»
15 years 7 months ago
Applying an authentic, dynamic learning environment in real world business
This paper describes a dynamic computer-based business learning environment and the results from applying it in a real-world business organization. We argue for using learning too...
Timo Lainema, Sami Nurmi
184
Voted
ATAL
2007
Springer
16 years 1 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
181
Voted
ATAL
2006
Springer
15 years 10 months ago
Learning trust strategies in reputation exchange networks
An agent's trust decision strategy consists of the agent's policies for making trust-related decisions, such as who to trust, how trustworthy to be, what reputations to ...
Karen Fullam, K. Suzanne Barber