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Hi, Thank you for providing the base code for running simulations and training agents.
But for training RL-based agents, we need to able to reset the environment ( lets say in kevindale_bare) after end of each episode. This needs a better implementation of reset() in gym_env, especially the TODO part as noted below.
I would not mind implementing the same and need your help to jump-start the process.
Please provide suggestions :D
TODO: Scenario config here:
# if self.scenario:
# world.configure(scenario)
# else:
The text was updated successfully, but these errors were encountered:
Hi, Thank you for providing the base code for running simulations and training agents.
But for training RL-based agents, we need to able to reset the environment ( lets say in kevindale_bare) after end of each episode. This needs a better implementation of reset() in gym_env, especially the TODO part as noted below.
I would not mind implementing the same and need your help to jump-start the process.
Please provide suggestions :D
TODO: Scenario config here:
The text was updated successfully, but these errors were encountered: