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Reinforcement Learning implementations for Carla simulator

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carla-rl

  • Reinforcement Learning implementations for Carla simulator https://github.com/carla-simulator/carla.

  • So far, it is implemented the dueling deep-Q learning with prioritized experience replay

  • Tested on carla version 0.9.5

How to run

  • Clone the project inside PythonAPI examples folder: carla_folder/PythonAPI/examples
  • Edit rl_config.py with the necessary hyperparameters
  • Run rl_agent.py. The possible arguments are listed below
  • After training, the resulting model can be tested by running rl_agent.py --test

rl_agent arguments

The arguments are adapted from manual_control.py, with minor changes

  • '--test': test a trained model
  • '-v', '--verbose': print debug information
  • '--host' (default='127.0.0.1'): IP of the host server
  • '-p', '--port' (default=2000): TCP port to listen to
  • '-a', '--autopilot': enable autopilot
  • '--res' (default='800x600'): window resolution
  • '--filter' (default='vehicle.audi.tt'): 'actor filter
  • '--rolename' (default='hero'): actor role name

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