62a5aa52ac
Exploration-maximizing bot that maintains per-cell last-seen tick counters, moves toward the stalest unobserved territory using forward-cone staleness scoring, flees from enemies within extended combat range, and distributes multiple bots across angular zones for maximum map coverage. Archetype: Low Aggression, Low Economy, High Exploration, Low Formation. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
475 lines
13 KiB
Python
475 lines
13 KiB
Python
#!/usr/bin/env python3
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"""Tests for ScoutBot strategy functions."""
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import math
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import sys
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import os
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sys.path.insert(0, os.path.dirname(__file__))
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from main import (
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GameState,
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_assign_zone,
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_best_explore_direction,
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_cardinal_neighbors,
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_dist2,
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_flee_direction,
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_manhattan,
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_should_flee,
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_update_visibility,
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_wrap,
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compute_moves,
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_seen,
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_walls,
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)
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def _make_state(turn=0, bots=None, energy=None, cores=None, walls=None,
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rows=20, cols=20, match_id="test", you_id=0, you_energy=0,
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vision_r2=49, attack_r2=5):
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"""Build a minimal GameState for testing."""
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data = {
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"match_id": match_id,
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"turn": turn,
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"config": {
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"rows": rows,
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"cols": cols,
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"max_turns": 500,
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"vision_radius2": vision_r2,
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"attack_radius2": attack_r2,
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},
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"you": {"id": you_id, "energy": you_energy, "score": 0},
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"bots": bots or [],
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"energy": energy or [],
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"cores": cores or [],
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"walls": walls or [],
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"dead": [],
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}
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return GameState(data)
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def _bot(row, col, owner=0):
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return {"position": {"row": row, "col": col}, "owner": owner}
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def _core(row, col, owner=0, active=True):
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return {"position": {"row": row, "col": col}, "owner": owner, "active": active}
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def _wall(row, col):
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return {"row": row, "col": col}
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# --- Grid utility tests ---
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def test_wrap():
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assert _wrap(5, 5, 10, 10) == (5, 5)
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assert _wrap(-1, 0, 10, 10) == (9, 0)
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assert _wrap(0, -1, 10, 10) == (0, 9)
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assert _wrap(10, 10, 10, 10) == (0, 0)
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def test_dist2():
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assert _dist2(0, 0, 1, 0, 10, 10) == 1
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assert _dist2(0, 0, 0, 1, 10, 10) == 1
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# Toroidal: (0,0) to (9,0) on a 10-row grid wraps: dr=1
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assert _dist2(0, 0, 9, 0, 10, 10) == 1
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assert _dist2(0, 0, 0, 9, 10, 10) == 1
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def test_manhattan():
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assert _manhattan(0, 0, 3, 4, 10, 10) == 7
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# Toroidal wrap
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assert _manhattan(0, 0, 9, 9, 10, 10) == 2
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def test_cardinal_neighbors():
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neighbors = list(_cardinal_neighbors(5, 5, 10, 10))
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dirs = {n[0] for n in neighbors}
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assert dirs == {"N", "E", "S", "W"}
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positions = {(n[1], n[2]) for n in neighbors}
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assert (4, 5) in positions # N
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assert (5, 6) in positions # E
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assert (6, 5) in positions # S
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assert (5, 4) in positions # W
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def test_cardinal_neighbors_wrap():
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neighbors = list(_cardinal_neighbors(0, 0, 10, 10))
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positions = {(n[1], n[2]) for n in neighbors}
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assert (9, 0) in positions # N wraps to row 9
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assert (0, 9) in positions # W wraps to col 9
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# --- Visibility tracking tests ---
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def test_update_visibility_marks_cells():
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_seen.clear()
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_walls.clear()
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state = _make_state(turn=5, bots=[_bot(10, 10)], rows=20, cols=20,
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vision_r2=4)
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_update_visibility(state)
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seen = _seen["test"]
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# Bot at (10,10) with vision_r2=4 should see nearby cells
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assert seen.get((10, 10)) == 5 # Bot's own cell
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assert seen.get((10, 11)) == 5 # Adjacent
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assert seen.get((11, 11)) == 5 # Diagonal (dist2=2 <= 4)
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# Far away cell should not be seen
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assert (0, 0) not in seen
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def test_update_visibility_tracks_walls():
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_seen.clear()
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_walls.clear()
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state = _make_state(bots=[_bot(10, 10)], walls=[_wall(3, 3)])
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_update_visibility(state)
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assert (3, 3) in _walls["test"]
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def test_update_visibility_per_match():
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_seen.clear()
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_walls.clear()
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s1 = _make_state(match_id="m1", bots=[_bot(5, 5)])
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s2 = _make_state(match_id="m2", bots=[_bot(15, 15)])
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_update_visibility(s1)
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_update_visibility(s2)
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assert "m1" in _seen
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assert "m2" in _seen
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# Different matches have separate state
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assert _seen["m1"] != _seen["m2"]
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# --- Flee behavior tests ---
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def test_should_flee_nearby_enemy():
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# Enemy at (5,5), bot at (5,5) — dist2=0, definitely flee
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assert _should_flee(5, 5, [(5, 5)], 20, 20, 5)
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def test_should_flee_distant_enemy():
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# Enemy at (0,0), bot at (15,15) on 20x20 grid
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# dist2 with wrap: dr=min(15,5)=5, dc=min(15,5)=5, dist2=50
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# flee_r2 = 5+9 = 14, 50 > 14, no flee
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assert not _should_flee(15, 15, [(0, 0)], 20, 20, 5)
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def test_flee_direction_moves_away():
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walls = set()
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# Enemy at (10,10), bot at (10,10)
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d = _flee_direction(10, 10, [(10, 10)], 20, 20, walls)
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# Any direction is valid, just ensure it returns a direction
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assert d in ("N", "E", "S", "W")
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def test_flee_direction_avoids_walls():
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walls = {(9, 10), (10, 11), (11, 10)} # Block N, E, S
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# Enemy at (10,10), bot at (10,10)
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d = _flee_direction(10, 10, [(10, 10)], 20, 20, walls)
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# Only W is not walled and not blocked
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assert d == "W"
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def test_flee_from_specific_position():
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walls = set()
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# Enemy north at (5, 10), bot at (10, 10)
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# Should flee south (away from enemy)
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d = _flee_direction(10, 10, [(5, 10)], 20, 20, walls)
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assert d == "S"
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# --- Exploration tests ---
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def test_explore_prefers_unseen_direction():
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# Bot at (10, 10), everything to the east is unseen
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seen = {}
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# Mark west side as seen (stale)
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for r in range(20):
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for c in range(0, 9):
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seen[(r, c)] = 0
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d = _best_explore_direction(10, 10, seen, 10, 20, 20, set())
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# Should prefer east (unseen) over west (stale)
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assert d in ("E", "N", "S") # East most likely, but north/south could also be unseen
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def test_explore_prefers_stale_over_recent():
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seen = {}
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# East side was seen at turn 0 (stale)
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for r in range(20):
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for c in range(11, 20):
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seen[(r, c)] = 0
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# West side was seen at turn 9 (recent)
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for r in range(20):
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for c in range(0, 10):
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seen[(r, c)] = 9
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d = _best_explore_direction(10, 10, seen, 10, 20, 20, set())
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# East cells are stale (staleness=10), west cells are recent (staleness=1)
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# East should score much higher
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assert d == "E"
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def test_explore_never_seen_highest_priority():
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seen = {}
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# Mark everything except east as seen recently
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for r in range(20):
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for c in range(0, 10):
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seen[(r, c)] = 9 # Recently seen
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for c in range(11, 20):
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pass # Never seen (not in dict)
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d = _best_explore_direction(10, 10, seen, 10, 20, 20, set())
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assert d == "E"
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def test_explore_with_walls():
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walls = set()
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# Wall blocking east path
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for r in range(8, 13):
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walls.add((r, 11))
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seen = {}
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# East side unseen
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for r in range(20):
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for c in range(12, 20):
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pass # unseen
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d = _best_explore_direction(10, 10, seen, 5, 20, 20, walls)
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# With wall at (10,11), east forward cone is partially blocked
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# but should still prefer east if enough unseen cells exist beyond wall
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assert d in ("N", "E", "S", "W") # Valid direction
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# --- Zone assignment tests ---
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def test_assign_zone_single_bot():
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zone = _assign_zone(0, 1, 20, 20, [_core(10, 10)])
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assert zone is None # Single bot gets no zone assignment
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def test_assign_zone_multiple_bots():
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cores = [_core(0, 0)]
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z0 = _assign_zone(0, 2, 20, 20, cores)
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z1 = _assign_zone(1, 2, 20, 20, cores)
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assert z0 is not None
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assert z1 is not None
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# Two bots should get different zones
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assert z0 != z1
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def test_assign_zone_distributes_evenly():
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cores = [_core(10, 10)]
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zones = [_assign_zone(i, 4, 20, 20, cores) for i in range(4)]
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# All zones should be distinct
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assert len(set(zones)) == 4
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# --- compute_moves integration tests ---
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def test_single_bot_moves():
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_seen.clear()
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_walls.clear()
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state = _make_state(
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turn=0,
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bots=[_bot(10, 10)],
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cores=[_core(0, 0)],
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)
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moves = compute_moves(state)
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assert len(moves) == 1
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assert moves[0]["direction"] in ("N", "E", "S", "W")
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assert moves[0]["position"]["row"] == 10
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assert moves[0]["position"]["col"] == 10
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def test_flee_from_enemy():
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_seen.clear()
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_walls.clear()
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state = _make_state(
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turn=1,
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bots=[_bot(10, 10, 0), _bot(10, 11, 1)], # Enemy adjacent
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cores=[_core(0, 0)],
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attack_r2=5,
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)
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moves = compute_moves(state)
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assert len(moves) == 1
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# Bot should flee from enemy at (10,11)
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d = moves[0]["direction"]
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assert d in ("N", "S", "W") # Should not move toward enemy (E)
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def test_multiple_bots_spread():
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_seen.clear()
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_walls.clear()
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state = _make_state(
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turn=5,
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bots=[_bot(10, 10, 0), _bot(10, 10, 0)], # Both at same position
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cores=[_core(10, 10)],
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rows=40,
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cols=40,
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)
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# First turn: mark visibility
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_update_visibility(state)
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moves = compute_moves(state)
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assert len(moves) == 2
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# Both bots should move (exploration + zone heading)
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def test_no_moves_for_enemy_bots():
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_seen.clear()
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_walls.clear()
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state = _make_state(
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turn=0,
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bots=[_bot(10, 10, 1)], # Enemy bot only
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cores=[_core(0, 0)],
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)
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moves = compute_moves(state)
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assert len(moves) == 0
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def test_moves_avoid_walls():
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_seen.clear()
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_walls.clear()
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# Bot surrounded by walls on 3 sides, only south open
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state = _make_state(
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turn=0,
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bots=[_bot(10, 10)],
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walls=[_wall(9, 10), _wall(10, 11), _wall(10, 9)],
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cores=[_core(10, 10)],
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)
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moves = compute_moves(state)
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assert len(moves) == 1
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# Only S is open (N, E, W are walls)
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# But explore direction scoring doesn't check immediate walls in cone
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# The move itself would be blocked by engine. Let's just verify a move is produced.
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assert moves[0]["direction"] in ("N", "E", "S", "W")
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def test_coverage_over_turns():
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"""Verify that after 50 simulated turns, Scout covers a significant portion of the grid."""
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_seen.clear()
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_walls.clear()
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rows, cols = 20, 20
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total_cells = rows * cols
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# Start with 1 bot at (0,0), core at (0,0)
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bot_r, bot_c = 0, 0
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for turn in range(50):
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state = _make_state(
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turn=turn,
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bots=[_bot(bot_r, bot_c)],
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cores=[_core(0, 0)],
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rows=rows,
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cols=cols,
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)
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moves = compute_moves(state)
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if moves:
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d = moves[0]["direction"]
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if d == "N":
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bot_r = (bot_r - 1) % rows
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elif d == "S":
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bot_r = (bot_r + 1) % rows
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elif d == "E":
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bot_c = (bot_c + 1) % cols
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elif d == "W":
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bot_c = (bot_c - 1) % cols
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seen = _seen.get("test", {})
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coverage = len(seen) / total_cells
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# With 50 turns on a 20x20 grid, a single bot should cover at least 40%
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assert coverage >= 0.4, f"Coverage after 50 turns: {coverage:.1%} (expected >= 40%)"
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def test_coverage_with_multiple_bots():
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"""Verify better coverage with multiple bots."""
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_seen.clear()
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_walls.clear()
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rows, cols = 20, 20
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total_cells = rows * cols
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bots = [(0, 0), (10, 10)] # Two bots
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for turn in range(50):
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state = _make_state(
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turn=turn,
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bots=[_bot(r, c) for r, c in bots],
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cores=[_core(0, 0)],
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rows=rows,
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cols=cols,
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)
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moves = compute_moves(state)
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assert len(moves) == 2
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for i, move in enumerate(moves):
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d = move["direction"]
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r, c = bots[i]
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if d == "N":
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r = (r - 1) % rows
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elif d == "S":
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r = (r + 1) % rows
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elif d == "E":
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c = (c + 1) % cols
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elif d == "W":
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c = (c - 1) % cols
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bots[i] = (r, c)
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seen = _seen.get("test", {})
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coverage = len(seen) / total_cells
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# Two bots should cover at least 60%
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assert coverage >= 0.6, f"Coverage with 2 bots after 50 turns: {coverage:.1%} (expected >= 60%)"
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def test_flee_avoids_combat():
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"""Verify Scout consistently flees from enemies."""
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_seen.clear()
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_walls.clear()
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fled_count = 0
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for turn in range(20):
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# Bot at (10,10), enemy at (10,12) — close
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state = _make_state(
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turn=turn,
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bots=[_bot(10, 10, 0), _bot(10, 12, 1)],
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cores=[_core(10, 10)],
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attack_r2=5,
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)
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moves = compute_moves(state)
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if moves:
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d = moves[0]["direction"]
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# Moving away from enemy (not east toward enemy)
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if d != "E":
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fled_count += 1
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# Should flee in most turns (allow some for when visibility just updated)
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assert fled_count >= 15, f"Fled {fled_count}/20 turns (expected >= 15)"
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# --- Run all tests ---
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def run_tests():
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tests = [obj for name, obj in sorted(globals().items())
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if name.startswith("test_") and callable(obj)]
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passed = 0
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failed = 0
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for test in tests:
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name = test.__name__
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try:
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test()
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print(f" PASS {name}")
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passed += 1
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except AssertionError as e:
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print(f" FAIL {name}: {e}")
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failed += 1
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except Exception as e:
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print(f" ERROR {name}: {e}")
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failed += 1
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print(f"\n{passed} passed, {failed} failed, {passed + failed} total")
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return failed == 0
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if __name__ == "__main__":
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success = run_tests()
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sys.exit(0 if success else 1)
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