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endgame option to influence and territory

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Sander Land committed 2020-05-09 22:51:36 +02:00
1 parent abc21943b5
commit f4e3624758
2 files changed
+15 -8
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config.json
+5 -3
View File
@@ -101,7 +101,7 @@
"stddev": 7.5,
"pick_n": 5,
"pick_frac": 0.5,
"endgame": 0.5,
"endgame": 0.45,
"_help_left": "Samples `pick_n + pick_frac * <number of legal moves>` away from the last move and plays the best one.",
"_help_right": "Increase `stddev` makes it prefer moves further away. Stops tenukiing after the 'endgame' fraction of the board is filled."
},
@@ -111,8 +111,9 @@
"pick_frac": 0.4,
"threshold": 3.5,
"line_weight": 10,
"endgame": 0.4,
"_help_left": "Samples `pick_n + pick_frac * <number of legal moves>` and plays the best one, biased to above the `threshold` line.",
"_help_right": "Increase `line_weight` to penalize moves near the edge more."
"_help_right": "Increase `line_weight` to penalize moves near the edge more. Stops strategy after the 'endgame' fraction of the board is filled."
},
"P:Territory": {
"pick_override": 0.95,
@@ -120,8 +121,9 @@
"pick_frac": 0.4,
"threshold": 3.5,
"line_weight": 2,
"endgame": 0.4,
"_help_left": "Samples `pick_n + pick_frac * <number of legal moves>` and plays the best one, biased to below the `threshold` line.",
"_help_right": "Increase `line_weight` to penalize moves closer to the center more."
"_help_right": "Increase `line_weight` to penalize moves closer to the center more. Stops strategy after the 'endgame' fraction of the board is filled."
}
},
"board_ui": {
core/ai.py
+10 -5
View File
@@ -95,13 +95,18 @@ def ai_move(game: Game, ai_mode: str, ai_settings: Dict) -> Tuple[Move, GameNode
legal_policy_moves = [(pol, mv) for pol, mv in policy_moves if not mv.is_pass if pol > 0]
n_moves = int(ai_settings["pick_frac"] * len(legal_policy_moves) + ai_settings["pick_n"])
if "influence" in ai_mode or "territory" in ai_mode:
thr_line = ai_settings["threshold"] - 1 # zero-based
if "influence" in ai_mode:
weight = lambda x, y: (1 / ai_settings["line_weight"]) ** (max(0, thr_line - min(size[0] - 1 - x, x)) + max(0, thr_line - min(size[1] - 1 - y, y)))
if cn.depth >= ai_settings["endgame"] * size[0] * size[1]:
weighted_coords = [(policy_grid[y][x], 1, x, y) for x in range(size[0]) for y in range(size[1]) if policy_grid[y][x] > 0]
ai_thoughts += f"Generated equal weights as move number >= {ai_settings['endgame'] * size[0] * size[1]}. "
else:
weight = lambda x, y: (1 / ai_settings["line_weight"]) ** (max(0, min(size[0] - 1 - x, x, size[1] - 1 - y, y) - thr_line))
weighted_coords = [(policy_grid[y][x] * weight(x, y), weight(x, y), x, y) for x in range(size[0]) for y in range(size[1]) if policy_grid[y][x] > 0]
ai_thoughts += f"Generated weights for {ai_mode} according to weight factor {ai_settings['line_weight']} and distance from {thr_line+1}th line. "
if "influence" in ai_mode:
weight = lambda x, y: (1 / ai_settings["line_weight"]) ** (max(0, thr_line - min(size[0] - 1 - x, x)) + max(0, thr_line - min(size[1] - 1 - y, y)))
else:
weight = lambda x, y: (1 / ai_settings["line_weight"]) ** (max(0, min(size[0] - 1 - x, x, size[1] - 1 - y, y) - thr_line))
weighted_coords = [(policy_grid[y][x] * weight(x, y), weight(x, y), x, y) for x in range(size[0]) for y in range(size[1]) if policy_grid[y][x] > 0]
ai_thoughts += f"Generated weights for {ai_mode} according to weight factor {ai_settings['line_weight']} and distance from {thr_line+1}th line. "
elif "local" in ai_mode or "tenuki" in ai_mode:
var = ai_settings["stddev"] ** 2
if not cn.move or cn.move.coords is None: