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ATAL
2008
Springer

Transfer of task representation in reinforcement learning using policy-based proto-value functions

8 years 4 months ago
Transfer of task representation in reinforcement learning using policy-based proto-value functions
Reinforcement Learning research is traditionally devoted to solve single-task problems. Therefore, anytime a new task is faced, learning must be restarted from scratch. Recently, several studies have addressed the issue of reusing the knowledge acquired in solving previous related tasks by transferring information about policies and value functions. In this paper, we analyze the use of proto-value functions under the transfer learning perspective. Proto-value functions are effective basis functions for the approximation of value functions defined over the graph obtained by a random walk on the environment. The definition of this graph is a key aspect in transfer transfer problems in which both the reward function and the dynamics change. Therefore, we introduce policy-based proto-value functions, which can be obtained by considering the graph generated by a random walk guided by the optimal policy of one of the tasks at hand. We compare the effectiveness of policy-based and standard p...
Eliseo Ferrante, Alessandro Lazaric, Marcello Rest
Added 12 Oct 2010
Updated 12 Oct 2010
Type Conference
Year 2008
Where ATAL
Authors Eliseo Ferrante, Alessandro Lazaric, Marcello Restelli
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