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Course project for CS294-112 Deep Reinforcement Learning in UC Berkeley in Fall 2018

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CS294-112 Final Project

Bridging Distribution Mismatch: Better Bound on Composable Deep Reinforcement Learning

Dependencies:

  • Python 3.5
  • Numpy version 1.14.5
  • TensorFlow version 1.10.5
  • OpenAI Gym version 0.10.5
  • seaborn
  • Box2D==2.3.2
  • OpenCV
  • ffmpeg
  • Vizdoom

Before doing anything, first replace gym/envs/box2d/lunar_lander.py with the provided lunar_lander.py file.

The code was based on an implementation of Q-learning in HW3.

This code can support Atari games and Vizdoom environments.

Instructions for Composable Soft Q Learning

python run_dqn_vizdoom.py --vizdoom --explore e-greedy --subgame shoot_monster
python run_dqn_vizdoom.py --vizdoom --explore soft_q --subgame avoid_shooters
python run_dqn_vizdoom.py --vizdoom --explore soft_q --ex2 --coef 1e-4 --subgame avoid_shooters

Cheers!

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Course project for CS294-112 Deep Reinforcement Learning in UC Berkeley in Fall 2018

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