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Validity Testing for Reinforcement Learning Projects

Discussion in 'ML-Agents' started by Drag_Neel, Jun 24, 2021.

  1. Drag_Neel

    Drag_Neel

    Joined:
    Mar 28, 2021
    Posts:
    1
    Hello,
    I want to know how I can do validity testing for a reinforcement learning project. I have done my undergrad thesis on reinforcement learning using Unity ML-Agents and submitted my work in a conference. One of the reviewers are saying that validity testing needs to be done. But I do not know how I can do validity testing for RL as I did not work with any datasets. My project was, "Character Animation using Reinforcement Learning and Imitation Learning Algorithms" where I used Unity ML-Agents to train a humanoid character to walk using the RL algorithm, PPO(Proximal Policy Optimization) and IL algorithms GAIL(Generative Adversarial Imitation Learning) and BC(Behavioral Cloning).

    WalkerRagdoll Walking.jpg
     
  2. ervteng_unity

    ervteng_unity

    Unity Technologies

    Joined:
    Dec 6, 2018
    Posts:
    150
    You're right, with RL, the simulator/game IS the dataset. However, you can test the reliability of your results by running the same experiments multiple times with different seeds, and take the average/standard deviation of the results - this is common practice. Usually for RL papers 5+ is the minimum number of runs. You can get this by changing the seed parameter in ML-Agents.
     
    Last edited: Jun 26, 2021