Utilization of Affordance by Reinforcement Learning Robot

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  • 強化学習ロボットによるアフォーダンスの利用
  • キョウカ ガクシュウ ロボット ニ ヨル アフォーダンス ノ リヨウ

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Abstract

The objective of this article is to provide the basic formulation of the affordance of environment. Study on affordance has been mostly focusing on the significance of perception, behavior and workspace, while leaving the problem of application unaddressed. Using the proposed method, it is possible to apply reinforcement learning algorithm on the robot within a certain environment, making the abstraction of affordance of the environment with interaction between the reinforcement learning agent and the environment available. Conclusion is made in the latter part of the paper that the percipient(robot) should simplify the number of perception in order to get enough valid equivalence relationship which abstracts affordance from environment with in the limit of incomplete perception; and the structure of the environment(workspace) would restrict the robot’s behavior. The prospect of this study, therefore, focuses on the interactive processes between the robot and the workspace from which the robot could set up it’s perception for particular tasks, and on how the robot could continuously manage it’s perception.

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