coolguyandClaude Opus 4.7 0f85fa85b3 Close librarian: full archive promote-survey + parallel dispatch
Second survey processed the remaining 12 archives via gemini after
the first batch of 3 was accepted. 12 drafts, 0 skips, 0 errors.
Every draft carries a deterministic Last-verified header
(2026-05-08, commit 5c221fb) thanks to the post-processing fix
landed in the previous commit. All 12 accepted into docs/research/
verbatim:

  deep-cfr-evaluation-profile-plan
  deep-cfr-legacy-experiment-reproduction
  deep-cfr-legacy-runtime-comparison
  deep-cfr-performance-experiments
  deep-cfr-profile-advantage-memory-split
  deep-cfr-profile
  deep-cfr-regret-fallback-audit
  deep-cfr-v0-gap-vs-coolrl
  deep-cfr-v0-plan
  fast-engine-next-optimizations
  post-a-optimization-calculus
  test-coverage-notes

docs/archive/ is now fully covered: every entry either has a
research counterpart by stem or by tail-match.

Also extracts _dispatch_one and adds --parallel N to
scripts/librarian_survey.py. ThreadPoolExecutor over the per-archive
work is safe because subprocess.run is network-bound (no GIL fight)
and each thread writes to its own output filename. Default stays
1 (sequential); --parallel 4 is the recommended speedup for large
surveys. The two surveys above ran sequentially; future runs can
opt in.

Plan declares librarian closed for new feature work. MEMORY drift
fixup and duplicate-merge modes stay deferred until a real input
surfaces. Stage 1 (5 deterministic checks) and Stage 2 (promote +
survey) remain operational.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-08 02:33:51 +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
Readme
7.7 MiB
Languages
Python 73.3%
Cython 21.7%
Julia 4.8%
Shell 0.2%