Reinforcement Learning Reading Group

RL is everywhere
(image taken from David Silver's Slides)
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The IITD Reinforcement Learning Reading Group is a student-run group that discusses research papers related to reinforcement learning.

The group is currently coordinated by Arindam Bhattacharya . It was founded by Ankit Anand and Arindam, under the supervision of Mausam.

This page provides information about group meetings. Also, it lists useful resources for reinforcement learning, and serves as a repository of all past readings.

New members are always welcome! Interested students or researchers may join the google group or slack team (slack is currently limited to domain. If you don't have an iitd email, contact arindam[at]

Next Meeting

Wednesday, 22 March, 2017. 4-5 PM
Room: SIT 113 (Committee Room)
Discussion Leader: Ankit.
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Reinforcement Learning Resources

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Suggested Readings for Future Meetings

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Spring 2017

  1. Deterministic Policy Gradient Algorithms
    David Silver, ICML, 2015
    Discussion leader: Ankit
  2. Actor Critic Methods
    Textbook, Chapter 13
    Discussion leader: Arindam
  3. Policy Gradient Methods for Reinforcement Learning with Function Approximation
    Richard S. Sutton, David McAllester, Satinder Singh, Yishay Mansour, NIPS 1999
    Discussion leader: Arindam.
  4. Simple statistical gradient-following algorithms for connectionist reinforcement learning
    RJ Williams - Machine learning, 1992
    Discussion leader: Arindam.
  5. Neural Architecture Search With Reinforcement Learning
    Barret Zoph, Quoc V. Le, ICLR 2017
    Discussion leader: Ankit.

Please report any broken links or inconsistencies to Arindam Bhattacharya.