coolguy
79f3ca0a58
이전 레포(../coolrl) commit 5a98855, da0d4cd에서 시도된 regret_matching_epsilon 튜닝(eps1e3 → eps1e4)이 zero-pit 대응책이었고 1e-4가 best로 채택되어 현재 default 0.0001로 남아있음을 doc에 기록. 이 lever는 이미 당겨진 상태이며 R1의 새 zero-pit은 다른 원인 (opponent=discard_only가 만든 game-theoretic 균형)이라는 점 명시.
coolrl-lost-cities
Focused Lost Cities extraction from the legacy coolrl repository.
The current implementation starts with the classic two-player card game:
- classic 5-expedition rules by default
- Python/Cython game engine
- env wrapper
- random, discard-only, and safe-heuristic bots
- core rule, scoring, mask, env, canonical-state, bot, and GUI smoke tests
Training code, Deep CFR, learned-policy evaluation, GUI, and web client are intentionally outside the first port.
Development
uv run pytest tests/games/classic
uv run lost-cities-classic
For future GUI work, install the optional GUI dependencies:
uv sync --extra gui
Run the classic pygame GUI:
uv run lost-cities-classic-gui --mode pvc --bot safe-heuristic
The GUI uses the in-process Cython game engine.
Basic Usage
from coolrl_lost_cities.games.classic import GameState, build_bot, classic_config
state = GameState.new_game(classic_config(seed=1))
bot = build_bot("random", seed=1)
while not state.terminal:
state.apply_action(bot.act(state))
print(state.total_score(0), state.total_score(1))
See classic port notes for the current direction.