[fix] Add heuristic evaluation, fork detection, and Phase 1 win/block split to AI.
Minimax leaf nodes now return a positional score instead of 0, using playable-threat detection (±100), non-playable threats (±40), fork bonus (±200), two-in-a-row (±5), and center control (±3). Phase 1 is split into two passes so the AI never blocks when it can win. Game sequence is now auto-logged to the browser console on game end. Applied to all three implementations (C++, JS, Python). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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+20
-4
@@ -268,6 +268,7 @@ int8_t scanBoard() {
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int evaluateBoard(int8_t aiP, int8_t huP) {
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int score = 0;
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int aiThreats = 0, huThreats = 0;
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// Center column bonus
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for (int r = 0; r < ROWS; r++) {
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@@ -277,16 +278,27 @@ int evaluateBoard(int8_t aiP, int8_t huP) {
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// Score a window of 4 cells by piece counts
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auto scoreWindow = [&](int c, int r, int dc, int dr) -> int {
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int ai = 0, hu = 0;
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int ai = 0, hu = 0, emptyC = -1, emptyR = -1;
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for (int i = 0; i < 4; i++) {
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int8_t v = board[c + i * dc][r + i * dr];
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int cc = c + i * dc;
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int rr = r + i * dr;
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int8_t v = board[cc][rr];
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if (v == aiP) ai++;
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else if (v == huP) hu++;
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else { emptyC = cc; emptyR = rr; }
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}
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if (ai > 0 && hu > 0) return 0;
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if (ai == 3) return 50;
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if (ai == 3) {
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aiThreats++;
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bool playable = emptyR == 0 || board[emptyC][emptyR - 1] != 0;
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return playable ? 100 : 40;
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}
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if (ai == 2) return 5;
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if (hu == 3) return -50;
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if (hu == 3) {
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huThreats++;
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bool playable = emptyR == 0 || board[emptyC][emptyR - 1] != 0;
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return playable ? -100 : -40;
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}
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if (hu == 2) return -5;
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return 0;
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};
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@@ -296,6 +308,10 @@ int evaluateBoard(int8_t aiP, int8_t huP) {
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for (int r = 0; r < 3; r++) for (int c = 0; c < 4; c++) score += scoreWindow(c, r, 1, 1);
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for (int r = 3; r < 6; r++) for (int c = 0; c < 4; c++) score += scoreWindow(c, r, 1, -1);
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// Fork bonus: multiple threats are disproportionately dangerous
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if (aiThreats >= 2) score += 200;
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if (huThreats >= 2) score -= 200;
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return score;
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}
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