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tianshou

thu-ml / tianshou

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How to support multi-agent reinforcement learning

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youkaichao
youkaichao commented Jul 9, 2020
  • I have marked all applicable categories:
    • exception-raising bug
    • RL algorithm bug
    • documentation request (i.e. "X is missing from the documentation.")
    • new feature request
  • I have visited the [source website], and in particular read the [known issues]
  • I have searched through the [issue tracker] and [issue categories] for duplicates
  • [ ]
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discussion good first issue

omerbsezer / Reinforcement_learning_tutorial_with_demo

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Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..

machine-learning tutorial reinforcement-learning deep-reinforcement-learning q-learning pomdps policy-gradient sarsa a3c dynamic-programming imitation-learning dyna td-learning actor-critic meta-learning
  • Updated Jan 22, 2019
  • Jupyter Notebook

chauvinSimon / My_Bibliography_for_Research_on_Autonomous_Driving

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Personal notes about scientific and research works on "Decision-Making for Autonomous Driving"

reinforcement-learning bibliography end-to-end decision-making prediction planning intention mdp mcts game-theory behavioral-cloning interaction risk-assessment imitation-learning inverse-reinforcement-learning pomdp decision-making-under-uncertainty carla model-based-reinforcement-learning belief-planning
  • Updated Nov 13, 2020

merantix / imitation-learning

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Run without docker, e.g. in a virtualenv

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markus-hinsche
markus-hinsche commented Dec 11, 2018

Currently you have to use docker to run this.

In order to make native version work, we could provide virtualenv instructions, e.g.:

  • pip install -r requirements.txt
  • install pip install tensorflow==1.12.0
  • change paths from /data
  • PYTHONPATH needs to be set correctly
  • Make sure everything runs by running pytest

Note that we haven't tested this yet.

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enhancement good first issue

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