Diversity Is All You Need (DIAYN) Implementation using RLkit
September 29, 2025 ยท View on GitHub
Implementation of Proximal Diversity Is All You Need (DIAYN) using the reinforcement learning framework RLKit by vitchyr. Installation for RLKit is specified in the original README for RLKit.
-
Diversity Is All You Need (DIAYN)
-
Proximal Policy Optimization (PPO)
- Example script
- Paper
- Other References
Running the Example Script for DIAYN
First, run the following command for training the sub-policies:
python examples/diayn.py <NAME_OF_ENVIRONMENT>
In addition, you can specify the number of skills that DIAYN is going to learn. The default is set at 10.
python examples/diayn.py <NAME_OF_ENVIRONMENT> --skill_dim <NUMBER_OF_SKILLS>
After training DIAYN, a file is saved onto data/DIAYN_<NUMBER_OF_SKILLS>_<ENVIRONMENT>_<DATE_AND_TIME>. Use the saved file to train the manager using PPO.
python examples/ppo_diayn.py <NAME_OF_ENVIRONMENT> <PATH_TO_SUB_POLICY>/params.pkl
Run the following command for visualizing the trained policies:
python scripts/run_policy_diayn.py <PATH_TO_SUB_POLICY>/params.pkl
Here is an example implementation result on the OpenAI Gym environment, Bipedal Walker-v2:

Intrinsic Reward Learning Curve:

Policy Loss Learning Curve:

Running the Example Script for PPO
Run the following command:
python examples/ppo.py
Here is an example implementation result on the OpenAI Gym environment, Bipedal Walker-v2:
