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An implementation of multi-agent TD3 with paddlepaddle and parl

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MATD3

An implementation of Multi-agent TD3.

Experiment Environment

A simple multi-agent particle world based on gym. Please see here to install and know more about the environment.

How to use

Dependencies:

Start Training:

# To train an agent for simple_speaker_listener scenario
python train.py

# To train for other scenario, model is automatically saved every 1000 episodes
python train.py --env [ENV_NAME]

# To show animation effects after training
python train.py --env [ENV_NAME] --show --restore

# To train and evaluate scenarios with continuous action spaces
python train.py --env [ENV_NAME] --continuous_actions
python train.py --env [ENV_NAME] --continuous_actions --show --restore

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An implementation of multi-agent TD3 with paddlepaddle and parl

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