4998931cb0
- Remove variant B (Brown cap, +1 for higher beating lower) from rules, engine, bots and simulator; a higher belt beating a lower one gains 0. - Final Exam: the defender fights as a Black belt (RULES.md v0.7). Ties to the defender and best-of-3 stay as simulator switches (`--exam`). - Report stripe income per source as gains and losses. - Add ten one-sidedness measures sampled at turn ends (lead gap, winner margin and lead share, halfway leader, last lead change, contention, rank swaps, leader Kumite losses, Exam challengers, winner pace). - Plan: decisions D28-D33 and the detailed Phase 6. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
132 lines
4.2 KiB
Python
132 lines
4.2 KiB
Python
"""Bot decisions on the fixture board (positions as in test_engine.py)."""
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import random
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import pytest
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from scripted import make_game, put
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from dojo.board import Board, Pos
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from dojo.bots import (
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AGGRESSIVE,
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BALANCED,
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FARMER,
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PROFILES,
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HeuristicAgent,
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Profile,
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RandomAgent,
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series_probability,
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win_probability,
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)
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from dojo.engine import Agent, FightView, Game, RandomSource
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from dojo.rules import DEFAULT_RULES, Card, RulesConfig
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ALLENAMENTO = Pos(0, 5)
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FATICA = Pos(3, 6)
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TATAMI = Pos(4, 4)
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DOJO_ENTRANCE = Pos(5, 7)
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DOJO = Pos(6, 7)
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def test_win_probability_counts_senshu_and_bonuses() -> None:
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assert win_probability(0, 0) == pytest.approx(21 / 36)
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assert win_probability(2, 0) == pytest.approx(30 / 36)
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assert win_probability(0, 2) == pytest.approx(10 / 36)
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assert win_probability(0, 0, senshu=False) == pytest.approx(15 / 36)
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def test_series_probability_is_a_best_of_n() -> None:
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assert series_probability(0.3, 1) == pytest.approx(0.3)
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assert series_probability(0.5, 3) == pytest.approx(0.5)
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assert series_probability(0.6, 3) == pytest.approx(0.6**2 * (3 - 2 * 0.6))
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def test_kiai_that_only_ties_the_exam_is_kept_when_ties_go_to_the_defender() -> None:
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game, _, _ = make_game(config=RulesConfig(exam_ties_to_defender=True))
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game.players[0].tecnica = Card.KIAI
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exam = FightView(0, 1, True, 3, 5, played=())
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assert not HeuristicAgent().play_tecnica(game.view(0), exam)
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assert HeuristicAgent().play_tecnica(game.view(0), fight(3, 5))
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def test_heuristic_prefers_allenamento_to_fatica() -> None:
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game, _, _ = make_game()
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choice = HeuristicAgent().choose_path(game.view(0), [(FATICA,), (ALLENAMENTO,)])
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assert choice == (ALLENAMENTO,)
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def test_brown_heuristic_takes_the_exam_when_it_can() -> None:
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game, _, _ = make_game()
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put(game, 0, DOJO_ENTRANCE, track=15)
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choice = HeuristicAgent().choose_path(game.view(0), [(ALLENAMENTO,), (DOJO,)])
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assert choice == (DOJO,)
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@pytest.mark.parametrize(("profile", "fights"), [(FARMER, False), (AGGRESSIVE, True)])
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def test_profiles_differ_on_an_even_fight(profile: Profile, fights: bool) -> None:
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game, _, _ = make_game()
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put(game, 0, Pos(4, 3), track=3)
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put(game, 1, TATAMI, track=3)
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choice = HeuristicAgent(profile).choose_path(game.view(0), [(Pos(5, 3),), (TATAMI,)])
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assert (choice == (TATAMI,)) is fights
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def fight(attacker_total: int, defender_total: int) -> FightView:
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return FightView(0, 1, False, attacker_total, defender_total, played=())
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@pytest.mark.parametrize(
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("me", "card", "totals", "plays"),
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[
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(0, Card.KIAI, (3, 5), True), # 5 ties 5: Senshu gives it to the attacker.
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(0, Card.KIAI, (2, 5), False), # Kiai cannot turn it: keep it.
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(0, Card.KIAI, (5, 5), False), # Already winning.
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(1, Card.KIAI, (5, 4), True), # The defender needs to beat, not tie.
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(1, Card.KIAI, (6, 4), False),
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(0, Card.KAESHI, (1, 6), True), # Losing: a reroll can only help.
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(1, Card.UKE, (4, 4), True),
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],
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)
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def test_heuristic_plays_a_tecnica_only_when_losing(
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me: int, card: Card, totals: tuple[int, int], plays: bool
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) -> None:
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game, _, _ = make_game()
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game.players[me].tecnica = card
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assert HeuristicAgent().play_tecnica(game.view(me), fight(*totals)) is plays
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def test_heuristic_keeps_the_tecnica_its_profile_ranks_first() -> None:
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game, _, _ = make_game()
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assert HeuristicAgent(BALANCED).keep_tecnica(game.view(0), Card.UKE, Card.KIAI) is Card.KIAI
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assert HeuristicAgent(FARMER).keep_tecnica(game.view(0), Card.UKE, Card.KIAI) is Card.UKE
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def play(board: Board, config: RulesConfig, seed: int) -> Game:
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rng = random.Random(seed)
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agents: list[Agent] = [HeuristicAgent(p) for p in PROFILES.values()]
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agents.append(RandomAgent(rng))
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game = Game(board, config, agents, RandomSource(seed))
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game.run()
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return game
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@pytest.mark.parametrize(
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"config",
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[
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DEFAULT_RULES,
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RulesConfig(exam_ties_to_defender=True, exam_defender_black=True, exam_rounds=3),
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],
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)
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def test_bots_play_full_games_reproducibly(board: Board, config: RulesConfig) -> None:
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first, again = play(board, config, seed=7), play(board, config, seed=7)
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assert first.winner is not None
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assert first.events == again.events
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