Reinforcement Learning
We provide some examples of MLPro’s RL funcionalities implementation, which is available on our GitHub file.
- Howto 01 - (RL) Types of reward
- Howto 02 - (RL) Run agent with own policy with gym environment
- Howto 03 - (RL) Train agent with own policy on gym environment
- Howto 04 - (RL) Run multi-agent with own policy in multicartpole environment
- Howto 05 - (RL) Train multi-agent with own policy on multicartpole environment
- Howto 10 - (RL) Train using SB3 Wrapper
- Howto 11 - (RL) Wrap mlpro Environment class to gym environment
- Howto 12 - (RL) Wrap mlpro Environment class to petting zoo environment
- Howto 13 - (RL) Comparison Native and Wrapper SB3 Policy
- Howto 14 - (RL) Train UR5 with SB3 wrapper
- Howto 15 - (RL) Train Robothtm with SB3 Wrapper