MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning

Authors

  • Manan Tomar Indian Institute of Technology Madras
  • Akhil Sathuluri Indian Institute of Technology Madras
  • Balaraman Ravindran Indian Institute of Technology Madras

DOI:

https://doi.org/10.1609/aaai.v33i01.330110053

Abstract

Generating a curriculum for guided learning involves subjecting the agent to easier goals first, and then gradually increasing their difficulty. This work takes a similar direction and proposes a dual curriculum scheme for solving robotic manipulation tasks with sparse rewards, called MaMiC. It includes a macro curriculum scheme which divides the task into multiple subtasks followed by a micro curriculum scheme which enables the agent to learn between such discovered subtasks. We show how combining macro and micro curriculum strategies help in overcoming major exploratory constraints considered in robot manipulation tasks without having to engineer any complex rewards and also illustrate the meaning and usage of the individual curricula. The performance of such a scheme is analysed on the Fetch environments.

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Published

2019-07-17

How to Cite

Tomar, M., Sathuluri, A., & Ravindran, B. (2019). MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 10053-10054. https://doi.org/10.1609/aaai.v33i01.330110053

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Section

Student Abstract Track