howto.rl.agent.004.rst

Howto RL-AGENT-004: Train Multi-Agent with Own Policy

.. automodule:: mlpro.rl.examples.howto_rl_agent_004_train_multiagent_with_own_policy_on_multicartpole_environment

Prerequisites

Please install the following packages to run this examples properly:

• OpenAI Gym

Executable code

.. literalinclude:: ../../../../../../../../src/mlpro/rl/examples/howto_rl_agent_004_train_multiagent_with_own_policy_on_multicartpole_environment.py
        :language: python

Results

Similar output as in :ref:`Howto RL-AGENT-002 <Howto Agent RL 002>` is displayed. However, three cartpole windows will be opened while the training log runs through. In addition, the training result folder will contain one more pkl file for the second agent.

Cross Reference

• :ref:`API Reference - RL Agent <target_api_rl_agents>`
• :ref:`API Reference - RL Environments <target_api_rl_env>`
• :ref:`API Reference - RL Scenario and Training <target_api_rl_run_train>`