9.2.1 - Rule-Based AI Action Layer (M9.2)

[SorraTheOrc]

Description

Implement rule-based AI strategies and actor that submit intents, log decisions, and support deterministic 100-tick runs.

Acceptance Criteria

• Strategies (balanced/aggressive/diplomatic) implemented
• AI actor submits valid intents and handles responses
• Regression test shows stabilization behavior
• Telemetry captures decision rationale

Dependencies

• ✅ Task 9.1.1 (AI Observer Foundation) - COMPLETED
• Action routing, intent schema

Priority

Medium

Recommended Owner

gamedev-agent

References

• See .pm/tracker.md Task 9.2.1 for full details
• Related: Issue 9.1.1 — AI Observer Foundation Review & Polish (M9.1) #19 (AI Observer Foundation)
• Implementation Plan: docs/simul/emergent_story_game_implementation_plan.md

Next Steps

1. Design strategy rules
2. Implement actor integration
3. Add regression tests and telemetry fields

[SorraTheOrc]

Task 9.2.1 verified complete and merged to main.

Verification Summary:

• ✅ Strategies implemented: BalancedStrategy, AggressiveStrategy, DiplomaticStrategy
• ✅ AI actor submits valid intents via submit_intent() and act() methods
• ✅ 112 tests passing (41 strategies + 34 actor + 37 observer)
• ✅ Telemetry captures decision rationale via StrategyDecision and ActionReceipt
• ✅ Documentation updated in README.md with AI Player Actor section
• ✅ Code merged to main in commits 61972c8, e1b8c1c

All acceptance criteria met. Closing issue.