coolguyandCodex 3e0a5db853 Prototype option b traversal interleaving
Add an experiment-only explicit-continuation traversal prototype that batches policy requests, records CPU/CUDA parity results, and updates the Option B plan with Phase 0/1 evidence.

Co-Authored-By: Codex <codex@openai.com>
2026-05-07 22:30:59 +09:00
2026-05-07 20:41:27 +09:00
2026-05-07 15:42:30 +09:00

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, passive-discard, 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.

S
Description
Lost Cities
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Cython 21.7%
Julia 4.8%
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