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name: gpi_action_selection description: Select USFA transfer actions by generalized policy improvement over candidate policy encodings.

GPI Action Selection

Use this skill when selecting actions for a new task w from conditioned successor features psi(s,a,z). It preserves the candidate set C and reports the winning candidate for mechanism evidence.

Inputs

• Target task weight w.
• Candidate encodings C.
• Action list.
• Successor-feature table for (state, action, z).

Outputs

• Selected action.
• Winning candidate encoding.
• Per-action and per-candidate score table.

Workflow

1. For every action and candidate z, compute psi(s,a,z)^T w.
2. Keep the best candidate for each action.
3. Choose the action with the largest candidate-backed score.
4. Log the full score table so recovery can prove candidate search occurred.

Validation

Run:

python tests/test_gpi.py

Limitations

This skill does not estimate successor features. It requires a table or approximator supplied by upstream USFA components.