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Reinforcement Learning implementations for Carla simulator https://github.com/carla-simulator/carla.
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So far, it is implemented the dueling deep-Q learning with prioritized experience replay
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Tested on carla version 0.9.5
- 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
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