Contributing: Policy

Policies live in plugrl-server.

Where to edit

• Implementation: plugrl_server/policy/...
• Registration: plugrl_server.policy.registration

Checklist

• Implement a policy and its config dataclass.
• Register it (UID + variants) and make sure it is imported.
• Keep action shapes stable across inference and training.
• Return actions batch-first with a horizon axis, (B, H, ...), and set action_dim and action_horizon in __init__. See the contract.

Verify

Start the server with your policy.

plugrl-run-server <your-policy> default dummy default

Connect a dummy worker.

plugrl-run-env-client dummy-v1 --num-episodes 1 --server-host 127.0.0.1 --server-port 8000

Troubleshooting

• Policy UID not listed: registration module was not imported.
• Shape mismatch in training: align the action, the runtime state (PolicyRuntimeState) and the train state your algorithm derives from it with your buffers.

Next steps

• Custom policy
• Contributing