Group 10 Final#83
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…nto one" This reverts commit ba936b2.
- Split Player10 into modular components (scoring.py, strategies.py, utils.py, config.py) - Add stochastic switch between original and altruism strategies - Implement spec-faithful selection forecasting with EWMA performance tracking - Add altruism gate with context-aware thresholds - Maintain full backward compatibility (ALTRUISM_USE_PROB=0.0 = original behavior) - Add comprehensive documentation and type hints - Clean, familiar file structure following existing codebase patterns
Core Fixes: - Fix coherence window logic to properly handle pause boundaries - Return -1.0 for empty context instead of 0.0 (matches official behavior) - Add detailed comments explaining old vs new behavior - Preserve old incorrect implementation in comments for reference Enhancements: - Add comprehensive debug logging configuration - Update hyperparameters to optimized values from Monte Carlo results - Switch to dynamic config imports for runtime updates - Add detailed performance tracking and decision logging - Document how OriginalStrategy benefits from coherence fix This resolves the core issue where Player10 was failing at coherence due to incorrect scoring that didn't match the official game rules.
- Add Monte Carlo experiments (monte_carlo.py) and runner (run_simulations.py) - Provide analysis helpers and quick demos (analyze_results.py, quick_demo.py, quick_debug_test.py) - Introduce flexible runner/examples for strategy tuning (flexible_runner.py, flexible_examples.py) - Add debug utilities and toggles (debug_utils.py, debug_toggle.py) - Include readmes documenting flexible framework and Monte Carlo approach - Add supporting scripts and tests (example_usage.py, test_framework.py, test_debug.py, demo.py) These tools support exploring Player10 strategies, hyperparameters, and debugging with reproducible experiments.
- Move READMEs to players/player_10/docs (README.md, FLEXIBLE_FRAMEWORK_README.md, MONTE_CARLO_README.md) - Move demos/examples to players/player_10/examples (demo.py, quick_demo.py, example_usage.py, flexible_examples.py) and fix relative imports - Move test scripts to players/player_10/tests (test_debug.py, quick_debug_test.py) - Move CLIs to players/player_10/tools (flexible_runner.py, run_simulations.py, debug_toggle.py) - Add short CLI aliases: tools/flex.py, tools/sim.py, tools/toggle.py, tools/analyze.py - Add __init__.py to new packages Context: building on 67a1461 (flex toolkit & debug utils) and 9b2308b (coherence & debugging), preserving core imports for player/strategies/debug_utils. Keeps analyze_results and monte_carlo as libraries for examples and tools.
- Move core agent code to players/player_10/agent and agent/logic - Move simulation libs to players/player_10/sim and analysis to players/player_10/analysis - Add re-exports so rom players.player_10 import Player10 remains stable - Update tools/examples/tests imports - Keep tools/, tests/, examples/, docs/ intact from previous commit Follows previous cleanup (e5f7092) and earlier enhancements (67a1461, 9b2308b).
…sults - Delete tools.sim, tools.run_simulations, tools.comprehensive_runner - Delete examples/demo.py, examples/quick_demo.py, examples/flexible_examples.py - Delete tests/quick_debug_test.py; keep test_debug.py - Update FLEXIBLE_FRAMEWORK_README migration notes (legacy runners removed) - Add .gitignore for simulation_results/ and players/player_10/results/
…in MONTE_CARLO_README - Parameters listed first with clear names - Single CLI for run and analyze documented - Mechanism summarized (combinations, metrics, output)
…xible framework doc
…layers, weights, EWMA_ALPHA, MIN_SAMPLED_PID; include overall mean/std; ensure values pulled from SimulationConfig
…ionConfig and display summaries correctly
…nner Top-10 summary and analysis improvements
- Removed 21 JSON result files from git tracking - Updated .gitignore to ignore all .json files - Results directory was already ignored but added explicit JSON pattern
Analysis of results - file not run yet, needs to be run in conjunction with other files
Add manual Monte Carlo dashboard and reporting fallbacks
…ashboard, robust reporting imports
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Finallllllll! |
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