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IPM
30
YEARS OLD

“School of Cognitive Sciences”

Paper   IPM / Cognitive Sciences / 13838
   School of Cognitive Sciences
  Title: Context Transfer and Q-Transferable Tasks
  Author(s):
1 . A. Mousavi
2 . B. Araabi
3 . M. Niliahmadabadi
  Status: In Proceedings
  Proceeding: Knowledge, Skill, and Behavior Transfer in Autonomous Robots: Papers from the 2015 AAAI Workshop
  Year: 2015
  Supported by: IPM
  Abstract:
This article discusses the notion of context transfer in reinforcement learning tasks. Context transfer, as defined in this article, implies knowledge transfer between tasks that share the same environment’s dynamics and reward function, but have different state and action spaces. For example, we have a working mobile robot in an environment. At some point, we decide to upgrade its sensors and/or actuators. Any change in these modules will result in a different description of the agentenvironment model, and the trained knowledge is no longer applicable. We consider the tasks of the old and new robots, as the source and target tasks, respectively. The Markov decision process (MDP) of these tasks, under certain conditions, are called Q-transferable tasks, and the problem of knowledge transfer between them is called context transfer.We investigate the relation of the MDPs of these tasks.

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