diff --git a/.gitignore b/.gitignore index 89cc49c..457f27a 100644 --- a/.gitignore +++ b/.gitignore @@ -3,3 +3,4 @@ .vscode/c_cpp_properties.json .vscode/launch.json .vscode/ipch +.vscode/settings.json \ No newline at end of file diff --git a/.vscode/settings.json b/.vscode/settings.json deleted file mode 100644 index 369420d..0000000 --- a/.vscode/settings.json +++ /dev/null @@ -1,9 +0,0 @@ -{ - "cSpell.words": [ - "espressif", - "fastled", - "lolin", - "microcontroller", - "paulstoffregen" - ] -} \ No newline at end of file diff --git a/Background information.md b/Background information.md new file mode 100644 index 0000000..7f37826 --- /dev/null +++ b/Background information.md @@ -0,0 +1,72 @@ +# 📑 Technical Specification: Connect 4 AI Logic + +## 1. Board Representation: The 2D Grid Model + +The game state is maintained in a 2D array of signed integers: `int8_t board[COLS][ROWS]`. This structure mirrors the physical dimensions of a standard Connect 4 rack. + +### Data Structure + +- **Dimensions:** 7 columns (X) by 6 rows (Y). +- **Mapping:** \* `0`: Null/Empty slot. + - `1`: Player 1 (Yellow / Human). + - `2`: Player 2 (Red / AI). +- **Hardware Translation:** To drive the 8x8 NeoPixel matrix, the 2D coordinates are flattened into a 1D index using the specific mapping: + $$Index = (y \times 8) + x$$ + _Note: The 8th column ($x=7$) is ignored by the game logic and reserved for UI borders._ + +--- + +## 2. Positional Evaluation + +Since Connect 4 has a state-space complexity of approximately $4.5 \times 10^{12}$, the ESP32 cannot calculate every possible outcome to the end of the game from the first move. Instead, it uses a **Heuristic Evaluation Function** to score board positions. + +### Scoring Heuristics + +1. **Terminal Victory:** Any move that results in a 4-in-a-row is valued at $+1000$ (for AI) or $-1000$ (for Human). +2. **Temporal Weighting:** To ensure the AI chooses the _fastest_ path to victory and the _longest_ path to defeat, the score is adjusted by the search depth: + - **AI Win:** $1000 + depth$ + - **Human Win:** $-1000 - depth$ +3. **Column Geometry:** The AI inherently values central columns higher than edges. This is not explicitly hardcoded in the score but emerges from the search logic: a disc in column 3 can be part of horizontal, vertical, and diagonal win lines in both directions, making it mathematically more valuable. + +--- + +## 3. Determining the Value of a "Half-Move" + +A "half-move" is a single disc placement by one player. Its value is determined via the **Minimax Algorithm** with **Alpha-Beta Pruning**. + +### The Recursive Search Process + +The AI simulates a move (a "branch") and then recursively simulates the opponent's best possible responses. The value of a move is the "minimized" maximum score possible from that branch. + +### Optimization: Alpha-Beta Pruning + +To prevent the ESP32-C3 from timing out, the engine "prunes" branches that are mathematically guaranteed to be worse than previously explored paths. + +- **Alpha ($\alpha$):** The best score the AI (Maximizer) can guarantee. +- **Beta ($\beta$):** The best score the Human (Minimizer) can guarantee. +- **The Cut-off:** If at any point $\beta \leq \alpha$, the branch is abandoned. + +### 4. Dynamic Move Ordering + +The efficiency of the value determination is heavily reliant on **Move Ordering**. By evaluating the most promising columns first (starting from the center), the AI finds a high "Alpha" value quickly. + +- **Search Order:** `3 -> 2 -> 4 -> 1 -> 5 -> 0 -> 6` + This ordering allows the Alpha-Beta pruning to discard up to 90% of the possible moves in the outer columns without calculating them, significantly reducing the "Thinking" time on the microcontroller. + +--- + +## 5. Summary of Logic Execution + +1. **Generate** all valid moves for the current board state. +2. **Order** moves starting from the center column. +3. **Execute** Minimax recursion for each move up to the current **Ply**. +4. **Prune** branches that cannot mathematically improve the current best option. +5. **Return** the move with the highest heuristic value. + +--- + +## References + +- [Information on how to analyze Connect-four](https://www.google.com/search?q=https://en.wikipedia.org/wiki/Connect_Four%23Mathematical_solution) +- [How does minimax work](https://en.wikipedia.org/wiki/Minimax) +- [What is aplpha-beta pruning](ttps://en.wikipedia.org/wiki/Alpha%E2%80%93beta_pruning) diff --git a/README.md b/README.md index 0d81643..df3d6e0 100644 --- a/README.md +++ b/README.md @@ -1,95 +1,86 @@ -# Connect Four: ESP32-C3 LED Edition +# 🕹ī¸ Connect 4 AI: Master Edition (v2.0) -A hardware-based Connect Four game featuring an 8x8 NeoPixel matrix, a strategic Minimax AI, and a dynamic "Attract Mode" for public display. - -## How the Program Works - -The program is built as a **Finite State Machine (FSM)**. -It manages the game flow by transitioning between distinct states based on user input, game outcomes, or inactivity timers. - -### 1. Game States - -- **Menu**: Displays stylized Roman numerals (**I** or **II**) to select between Single Player or Two Player modes. -- **Game Play**: The main loop handles the real-time gravity of falling discs, encoder tracking for column selection, and the hand-off between the human and the AI. -- **Game Over**: Triggered when a win or draw is detected. It "locks" the board, dims the background discs to 15% intensity, and flashes the winning line. -- **Demo Mode**: Triggered after 60 seconds of inactivity. The AI plays against itself to act as a visual "attract mode." - -### 2. Win Detection Logic - -To ensure 100% accuracy, the program performs a synchronous, multi-directional scan of the 7x6 grid after every single move. -It checks for four matching non-zero values in the following patterns: - -- **Horizontal**: `[column] [row]` to `[column + 3] [row]` -- **Vertical**: `[column] [row]` to `[column] [row + 3]` -- **Diagonal Up**: `[column] [row]` to `[column + 3] [row + 3]` -- **Diagonal Down**: `[column] [row]` to `[column + 3] [row - 3]` +A high-performance, feature-rich Connect 4 implementation for the ESP32-C3. This version features a "living" AI that evolves as you play, human-like movement animations, and a robust win-detection engine. --- -## The AI: Strategic Minimax +## 🛠 Hardware Configuration -The computer opponent uses the **Minimax Algorithm**, a classic artificial intelligence method for zero-sum games. +### 🔌 Pin Mapping (Lolin C3 Mini) -### 1. Look-Ahead (Depth Search) +| Component | ESP32-C3 Pin | Function | +| :------------------- | :----------- | :--------------- | +| **NeoPixel Matrix** | `GPIO 4` | Data Input (DIN) | +| **Rotary Encoder A** | `GPIO 0` | Directional CLK | +| **Rotary Encoder B** | `GPIO 1` | Directional DT | +| **Encoder Button** | `GPIO 2` | Selection (SW) | -The AI does not just look at the current board; it simulates the game **6 to 8 moves into the future**. -It explores a "tree" of possibilities: _"If I play here, and the player plays there, then I can play here..."_ +### 📐 Physical Layout -### 2. Alpha-Beta Pruning +The project is optimized for an 8x8 NeoPixel Matrix (65mm x 67mm). -Because searching millions of possibilities would be too slow for a microcontroller, we use **Alpha-Beta Pruning**. -This allows the AI to "prune" (ignore) branches of the game tree that are mathematically -guaranteed to be worse than moves it has already found, significantly speeding up the calculation. - -### 3. Immediate Threat Reaction - -To prevent the AI from being "distracted" by deep strategies while missing a simple win or loss, -we implemented a high-priority **Reaction Scanner**: - -- **Kill Move**: If the AI can win in exactly one move, it takes it immediately. -- **Block Move**: If the player is one move away from winning (3-in-a-row), the AI identifies the threat and blocks it regardless of the Minimax score. - -### 4. Controlled Randomness (Demo Mode) - -To keep the Demo Mode interesting for spectators, the AI has a 25% chance to ignore the "perfect" move and pick a random column. -This ensures that every demo game is unique and not a repetitive loop of the same strategy. +- **Row 0:** Interaction & AI Decision Visualization. +- **Row 1:** Static Blue UI border. +- **Rows 2-7:** Active $7 \times 6$ game board. +- **Status Column:** Far right column (Index 7) manages UI framing and "Glow" effects. --- -## Technical Specifications +## 🧠 Advanced AI & Logic Features -### Hardware Pins (Lolin C3 Mini) +### 1. Progressive Difficulty (Evolution Mode) -| Component | Pin | Function | -| :---------- | :-- | :--------------------------------------- | -| **LED_PIN** | 4 | WS2812B NeoPixel Data | -| **ENC_A** | 0 | Rotary Encoder Phase A | -| **ENC_B** | 1 | Rotary Encoder Phase B | -| **ENC_SW** | 2 | Switch (Includes 50ms Software Debounce) | +To keep the game challenging and the CPU efficient, the AI search depth (Ply) scales as the board fills. -### NeoPixel Grid Layout +- **Formula:** $DynamicPly = BasePly + \lfloor \frac{DiscsOnBoard}{7} \rfloor$ +- **Benefit:** The AI is "casual" in the opening but becomes a "Grandmaster" in the endgame when tactical precision is vital. -The 8x8 matrix is mapped as follows: +### 2. Intelligent Win Detection & Flashing -- **Play Area**: 7 columns (0-6) by 6 rows (0-5). -- **Boundaries**: Row 1 and Column 7 are lit in **Blue** to mark the board limits. -- **Indicators**: The top-right pixel (7,0) pulses in the computer's color while it is "thinking." -- **Glowing Frame**: During Demo mode, the blue borders pulse with a white "glow" effect using a `beat8` sine wave to indicate autonomous play. +The win-engine has been refactored to prevent "color ghosting." + +- **Winner Locking:** The `scanBoard()` function returns the specific ID of the winner (1 for Yellow, 2 for Red). +- **Flashing Accuracy:** The final animation uses this ID to ensure the winning 4-in-a-row flashes in the **correct player's color**, regardless of whose turn it was when the game ended. + +### 3. Smart Watchdog (Tiered Timeout) + +The game respects your "thinking time" by using a tiered idle-timeout system: + +- **Menu/Finished State:** Standard timeout (e.g., 60s). +- **Playing State:** **Double Timeout** (e.g., 120s). This gives human players more time to analyze complex boards before the game auto-resets to Demo Mode. + +### 4. Strategic Blunder Injection + +To ensure Demo Mode doesn't end in an infinite loop of draws, a 20% "Blunder Chance" is injected. This forces the AI to occasionally make a human-like mistake, creating openings for a definitive winner. --- -## Controls & Interaction +## 📖 Code Architecture & Modules -- **Rotate Encoder**: Move the cursor (top row) to select a column. -- **Press Encoder Button**: Drop a disc. -- **Full Column Warning**: If you attempt to play in a full column, the selection disc will blink rapidly, and the move will be ignored. -- **Reset**: After a game ends, press the button once to return to the Menu. +### 🔄 State Machine -## Build Flags (platformio.ini) +The core loop manages five distinct states: -Tweak the game performance without changing the source code: +1. **MENU:** Mode selection and board reset. +2. **PLAYING:** Active turn-based logic with gravity-accelerated drop animations. +3. **FINISHED_WIN:** Locks the winner ID and flashes the winning segment. +4. **FINISHED_DRAW:** Blinks the entire board to signify a stalemate. +5. **DEMO:** Auto-plays with randomized difficulty (Ply 3-6) and mandatory blunder logic. -- `IDLE_TIMEOUT`: Time (ms) before Demo Mode starts. -- `DEMO_RESET_PAUSE`: Delay (ms) between games in Demo Mode. -- `DEBOUNCE_DELAY`: Sensitivity of the encoder button. -- `BRIGHTNESS`: Global brightness of the NeoPixels. +### 🌐 Web Administration Portal + +Accessible via the **"Connect4-Config"** AP at `192.168.4.1`. + +- **Base Ply:** Sets the starting difficulty level. +- **Brightness:** Global LED intensity (0-255). +- **Evolution Toggle:** Turn on/off the progressive difficulty scaling. +- **Blunder Toggle:** Allow the AI to make mistakes during Human-vs-AI matches. + +--- + +## 🛠 Installation + +1. **Environment:** Use VS Code with the **PlatformIO** extension. +2. **Dependencies:** `FastLED`, `Encoder`, `Preferences`. +3. **Build Flag:** Define your WiFi password in `platformio.ini`: `-D WIFI_PASSWORD=\"your_password\"`. +4. **Flash:** Upload to your ESP32-C3 and enjoy the ultimate desktop Connect 4 experience. diff --git a/app.db b/app.db deleted file mode 100644 index e69de29..0000000 diff --git a/src/main.cpp b/src/main.cpp index 97ebe83..7df2ca5 100644 --- a/src/main.cpp +++ b/src/main.cpp @@ -9,6 +9,7 @@ const int COLS = 7; const int ROWS = 6; +// --- Configuration & Globals --- CRGB leds[NUM_LEDS]; Encoder myEnc(ENC_A, ENC_B); WebServer server(80); @@ -28,52 +29,47 @@ State gameState = MENU; int8_t menuMode = 0; int8_t currentPlayer = 1; +int8_t winnerPlayer = 0; // Tracks who actually won for the flashing effect int8_t activeCol = 3; long oldEncPos = -999; uint32_t lastActivityTime = 0; uint32_t demoResetTimer = 0; bool isDemoOver = false; +uint8_t demoPly = 4; -// Web-Configurable Parameters (Stored in Flash) uint8_t current_look_ahead; uint8_t current_brightness; uint32_t current_idle_timeout_ms; +bool blunder_enabled = false; +bool progressive_difficulty = false; -// Thinking Animation Helpers uint8_t aiBrightness = 0; bool aiFadeUp = true; -// --- Helper Functions --- -int getIdx(int x, int y) { return (y * 8) + x; } +// --- Function Prototypes --- +int getIdx(int x, int y); +void drawStaticUI(); +void renderBoard(); +int getFirstEmptyRow(int col); +bool isBoardFull(); +int8_t scanBoard(); // Changed to return the winner ID +void updateThinkingVisuals(int8_t p, int8_t col); +void animateDrop(int col, int player); +void moveDiscToCol(int startCol, int targetCol, int player, int speed); +int minimax(int depth, int alpha, int beta, bool isMax, int8_t aiP, int8_t huP, int8_t rootCol); +void performAiMove(int8_t aiP); +void showMenu(); +int getDynamicPly(); -void updateThinkingLED(int8_t p) -{ - static uint32_t lastCycle = 0; - if (millis() - lastCycle < 20) - return; - lastCycle = millis(); - if (aiFadeUp) - { - aiBrightness += 15; - if (aiBrightness >= 240) - aiFadeUp = false; - } - else - { - aiBrightness -= 15; - if (aiBrightness <= 15) - aiFadeUp = true; - } - CRGB compColor = (p == 1) ? CRGB::Yellow : CRGB::Red; - leds[getIdx(7, 0)] = compColor.nscale8(aiBrightness); - FastLED.show(); -} +// --- Utility & Rendering --- + +int getIdx(int x, int y) { return (y * 8) + x; } void drawStaticUI() { FastLED.clear(); CRGB borderColor = CRGB::Blue; - if (gameState == DEMO || (gameState >= 2 && isDemoOver)) + if (gameState == DEMO || gameState >= 2) { uint8_t glow = beat8(15); borderColor = blend(CRGB::Blue, CRGB::White, glow / 4); @@ -109,6 +105,80 @@ int getFirstEmptyRow(int col) return -1; } +int getDynamicPly() +{ + if (!progressive_difficulty && gameState != DEMO) + return current_look_ahead; + int count = 0; + for (int c = 0; c < COLS; c++) + for (int r = 0; r < ROWS; r++) + if (board[c][r] != 0) + count++; + return constrain(current_look_ahead + (count / 7), 1, 10); +} + +// --- Visuals & Animations --- + +void updateThinkingVisuals(int8_t p, int8_t col) +{ + static uint32_t lastCycle = 0; + if (millis() - lastCycle < 25) + return; + lastCycle = millis(); + if (aiFadeUp) + { + aiBrightness += 15; + if (aiBrightness >= 240) + aiFadeUp = false; + } + else + { + aiBrightness -= 15; + if (aiBrightness <= 15) + aiFadeUp = true; + } + for (int x = 0; x < COLS; x++) + leds[getIdx(x, 0)] = CRGB::Black; + CRGB aiColor = (p == 1) ? CRGB::Yellow : CRGB::Red; + leds[getIdx(col, 0)] = aiColor.nscale8(aiBrightness); + FastLED.show(); +} + +void animateDrop(int col, int player) +{ + int targetRow = getFirstEmptyRow(col); + if (targetRow == -1) + return; + for (int r = 5; r >= targetRow; r--) + { + renderBoard(); + leds[getIdx(col, 7 - r)] = (player == 1) ? CRGB::Yellow : CRGB::Red; + FastLED.show(); + delay(max(20, 80 - (5 - r) * 15)); + } + board[col][targetRow] = player; + renderBoard(); + FastLED.show(); +} + +void moveDiscToCol(int startCol, int targetCol, int player, int speed) +{ + int current = startCol; + CRGB pColor = (player == 1) ? CRGB::Yellow : CRGB::Red; + while (current != targetCol) + { + leds[getIdx(current, 0)] = CRGB::Black; + current += (targetCol > current) ? 1 : -1; + renderBoard(); + leds[getIdx(current, 0)] = pColor; + FastLED.show(); + delay(speed); + } + activeCol = targetCol; +} + +// --- AI Engine --- + bool isBoardFull() { for (int c = 0; c < COLS; c++) @@ -117,74 +187,85 @@ bool isBoardFull() return true; } -bool scanBoard(int8_t p) +int8_t scanBoard() { memset(winMask, 0, sizeof(winMask)); - bool found = false; - auto check = [&](int c, int r, int dc, int dr) + auto check = [&](int column, int row, int columnOffset, int rowOffset) { - if (board[c][r] == p && board[c + dc][r + dr] == p && board[c + 2 * dc][r + 2 * dr] == p && board[c + 3 * dc][r + 3 * dr] == p) + int8_t postion = board[column][row]; + if (postion != 0 && board[column + columnOffset][row + rowOffset] == postion && board[column + 2 * columnOffset][row + 2 * rowOffset] == postion && board[column + 3 * columnOffset][row + 3 * rowOffset] == postion) { - for (int i = 0; i < 4; i++) - winMask[getIdx(c + i * dc, 7 - (r + i * dr))] = true; - return true; + for (int index = 0; index < 4; index++) + winMask[getIdx(column + index * columnOffset, 7 - (row + index * rowOffset))] = true; + return postion; } - return false; + return (int8_t)0; }; - for (int r = 0; r < 6; r++) - for (int c = 0; c < 4; c++) - if (check(c, r, 1, 0)) - found = true; - for (int r = 0; r < 3; r++) - for (int c = 0; c < 7; c++) - if (check(c, r, 0, 1)) - found = true; - for (int r = 0; r < 3; r++) - for (int c = 0; c < 4; c++) - if (check(c, r, 1, 1)) - found = true; - for (int r = 3; r < 6; r++) - for (int c = 0; c < 4; c++) - if (check(c, r, 1, -1)) - found = true; - return found; + for (int row = 0; row < 6; row++) + for (int column = 0; column < 4; column++) + { + int8_t res = check(column, row, 1, 0); + if (res) + return res; + } + for (int row = 0; row < 3; row++) + for (int column = 0; column < 7; column++) + { + int8_t res = check(column, row, 0, 1); + if (res) + return res; + } + for (int row = 0; row < 3; row++) + for (int column = 0; column < 4; column++) + { + int8_t res = check(column, row, 1, 1); + if (res) + return res; + } + for (int row = 3; row < 6; row++) + for (int column = 0; column < 4; column++) + { + int8_t res = check(column, row, 1, -1); + if (res) + return res; + } + return 0; } -// --- AI Engine --- -int minimax(int depth, int alpha, int beta, bool isMax, int8_t aiP, int8_t huP) +int minimax(int depth, int alpha, int beta, bool isMax, int8_t aiPlayer, int8_t humanPlayer, int8_t rootCol) { if (depth >= current_look_ahead - 1) - updateThinkingLED(aiP); + updateThinkingVisuals(aiPlayer, rootCol); else yield(); - if (scanBoard(aiP)) + // Check for wins within minimax + int8_t win = scanBoard(); + if (win == aiPlayer) return 1000 + depth; - if (scanBoard(huP)) + if (win == humanPlayer) return -1000 - depth; if (depth == 0 || isBoardFull()) return 0; int order[] = {3, 2, 4, 1, 5, 0, 6}; int best = isMax ? -2000 : 2000; - for (int c : order) + for (int column : order) { - int r = getFirstEmptyRow(c); - if (r != -1) + int row = getFirstEmptyRow(column); + if (row != -1) { - board[c][r] = isMax ? aiP : huP; - int val = minimax(depth - 1, alpha, beta, !isMax, aiP, huP); - board[c][r] = 0; + board[column][row] = isMax ? aiPlayer : humanPlayer; + int val = minimax(depth - 1, alpha, beta, !isMax, aiPlayer, humanPlayer, (depth == current_look_ahead ? column : rootCol)); + board[column][row] = 0; if (isMax) { - if (val > best) - best = val; + best = max(best, val); alpha = max(alpha, best); } else { - if (val < best) - best = val; + best = min(best, val); beta = min(beta, best); } if (beta <= alpha) @@ -194,54 +275,109 @@ int minimax(int depth, int alpha, int beta, bool isMax, int8_t aiP, int8_t huP) return best; } -void performAiMove(int8_t aiP) +void performAiMove(int8_t aiPlayer) { - int8_t huP = (aiP == 1) ? 2 : 1; - aiBrightness = 0; - aiFadeUp = true; - for (int c = 0; c < COLS; c++) - { - int r = getFirstEmptyRow(c); - if (r != -1) - { - board[c][r] = aiP; - if (scanBoard(aiP)) - { - leds[getIdx(7, 0)] = CRGB::Black; - return; - } - board[c][r] = huP; - if (current_look_ahead >= 2 && scanBoard(huP)) - { - board[c][r] = aiP; - leds[getIdx(7, 0)] = CRGB::Black; - return; - } - board[c][r] = 0; - } - } + int humanPlayer = (aiPlayer == 1) ? 2 : 1; int bestScore = -30000; int bestCol = 3; - for (int c : {3, 2, 4, 1, 5, 0, 6}) + int originalPly = current_look_ahead; + current_look_ahead = (gameState == DEMO) ? demoPly : getDynamicPly(); + + for (int column = 0; column < COLS; column++) { - int r = getFirstEmptyRow(c); - if (r != -1) + int row = getFirstEmptyRow(column); + if (row != -1) { - board[c][r] = aiP; - int score = minimax(current_look_ahead, -30000, 30000, false, aiP, huP); - board[c][r] = 0; + board[column][row] = aiPlayer; + if (scanBoard() == aiPlayer) + { + board[column][row] = 0; + bestCol = column; + goto finalize; + } + board[column][row] = humanPlayer; + if (current_look_ahead >= 2 && scanBoard() == humanPlayer) + { + board[column][row] = 0; + bestCol = column; + goto finalize; + } + board[column][row] = 0; + } + } + for (int column : {3, 2, 4, 1, 5, 0, 6}) + { + int row = getFirstEmptyRow(column); + if (row != -1) + { + board[column][row] = aiPlayer; + int score = minimax(current_look_ahead, -30000, 30000, false, aiPlayer, humanPlayer, column); + board[column][row] = 0; if (score > bestScore) { bestScore = score; - bestCol = c; + bestCol = column; } } } - board[bestCol][getFirstEmptyRow(bestCol)] = aiP; - leds[getIdx(7, 0)] = CRGB::Black; + if ((gameState == DEMO || blunder_enabled) && random(100) < 20) + { + int rCol = random(0, 7); + if (getFirstEmptyRow(rCol) != -1) + bestCol = rCol; + } +finalize: + current_look_ahead = originalPly; + moveDiscToCol(activeCol, bestCol, aiPlayer, 100); + delay(450); + animateDrop(bestCol, aiPlayer); +} + +// --- Web Portal --- + +void handleRoot() +{ + String html = "" + ""; + html += "

Connect 4 Admin

"; + html += "Base AI Ply (1-10):"; + html += "Brightness (5-255):"; + html += "Idle Timeout (Sec):"; + html += "Enable Blunders:
"; + html += "Evolution Mode:

"; + html += "
"; + server.send(200, "text/html", html); +} + +void handleSave() +{ + if (server.hasArg("ply")) + { + current_look_ahead = server.arg("ply").toInt(); + prefs.putUChar("ply", current_look_ahead); + } + if (server.hasArg("br")) + { + current_brightness = server.arg("br").toInt(); + FastLED.setBrightness(current_brightness); + prefs.putUChar("br", current_brightness); + } + if (server.hasArg("idle")) + { + uint32_t s = server.arg("idle").toInt(); + current_idle_timeout_ms = s * 1000; + prefs.putUInt("idle", s); + } + blunder_enabled = server.hasArg("blunder"); + prefs.putBool("blunder", blunder_enabled); + progressive_difficulty = server.hasArg("evolve"); + prefs.putBool("evolve", progressive_difficulty); + server.sendHeader("Location", "/"); + server.send(303); } -// --- Menu UI with Restored Serifs --- void showMenu() { isDemoOver = false; @@ -279,42 +415,6 @@ void showMenu() FastLED.show(); } -// --- Web Portal --- -void handleRoot() -{ - String html = ""; - html += ""; - html += "

Connect 4 Admin

"; - html += "AI Ply (1-10):"; - html += "Brightness (5-255):"; - html += "Idle Timeout (Sec):"; - html += "
"; - server.send(200, "text/html", html); -} - -void handleSave() -{ - if (server.hasArg("ply")) - { - current_look_ahead = server.arg("ply").toInt(); - prefs.putUChar("ply", current_look_ahead); - } - if (server.hasArg("br")) - { - current_brightness = server.arg("br").toInt(); - FastLED.setBrightness(current_brightness); - prefs.putUChar("br", current_brightness); - } - if (server.hasArg("idle")) - { - uint32_t s = server.arg("idle").toInt(); - current_idle_timeout_ms = s * 1000; - prefs.putUInt("idle", s); - } - server.sendHeader("Location", "/"); - server.send(303); -} - void setup() { Serial.begin(115200); @@ -322,29 +422,16 @@ void setup() current_look_ahead = prefs.getUChar("ply", 8); current_brightness = prefs.getUChar("br", 25); current_idle_timeout_ms = prefs.getUInt("idle", 60) * 1000; + blunder_enabled = prefs.getBool("blunder", false); + progressive_difficulty = prefs.getBool("evolve", false); FastLED.addLeds(leds, NUM_LEDS); FastLED.setBrightness(current_brightness); pinMode(ENC_SW, INPUT_PULLUP); - - WiFi.disconnect(true); // Clear old settings - WiFi.mode(WIFI_AP); // Force Access Point mode - delay(100); // Give the radio a moment to reset - - // SSID, Password (MUST be 8+ chars), Channel, Hidden (0=No), Max Clients - if (WiFi.softAP("Connect4-Config", WIFI_PASSWORD, 1, 0, 4)) - { - Serial.println("WPA2 AP Started Successfully"); - } - else - { - Serial.println("AP Failed - Check if WIFI_PASSWORD is at least 8 characters!"); - } - + WiFi.softAP("Connect4-Config", WIFI_PASSWORD); server.on("/", handleRoot); server.on("/save", HTTP_POST, handleSave); server.begin(); - lastActivityTime = millis(); showMenu(); } @@ -355,18 +442,17 @@ void loop() long newPos = myEnc.read() / SENSITIVITY; bool pressed = (digitalRead(ENC_SW) == LOW); - // Escape Demo / Interrupt if (newPos != oldEncPos || (pressed && (millis() - lastActivityTime > 500))) { - if (gameState == DEMO || isDemoOver) + if (gameState >= 2 || gameState == DEMO) { - for (int i = 0; i < 10; i++) + for (int index = 0; index < 10; index++) { fadeToBlackBy(leds, NUM_LEDS, 32); FastLED.show(); delay(30); } - delay(2000); + delay(500); gameState = MENU; memset(board, 0, sizeof(board)); showMenu(); @@ -377,6 +463,16 @@ void loop() lastActivityTime = millis(); } + uint32_t activeLimit = (gameState == PLAYING) ? (current_idle_timeout_ms * 2) : current_idle_timeout_ms; + if (gameState != DEMO && (gameState < 2) && (millis() - lastActivityTime > activeLimit)) + { + gameState = DEMO; + memset(board, 0, sizeof(board)); + currentPlayer = 1; + demoPly = random(3, 7); + return; + } + if (gameState == MENU) { if (newPos != oldEncPos) @@ -400,12 +496,6 @@ void loop() } delay(300); } - if (millis() - lastActivityTime > current_idle_timeout_ms) - { - gameState = DEMO; - memset(board, 0, sizeof(board)); - currentPlayer = 1; - } } else if (gameState == PLAYING) { @@ -422,28 +512,35 @@ void loop() int row = getFirstEmptyRow(activeCol); if (row != -1) { - board[activeCol][row] = currentPlayer; - renderBoard(); - FastLED.show(); - if (scanBoard(currentPlayer)) + animateDrop(activeCol, currentPlayer); + winnerPlayer = scanBoard(); + if (winnerPlayer != 0) + { gameState = FINISHED_WIN; + demoResetTimer = millis(); + } else if (isBoardFull()) + { gameState = FINISHED_DRAW; + demoResetTimer = millis(); + } else { if (menuMode < 2) { - int8_t aiP = (menuMode == 0) ? 2 : 1; - performAiMove(aiP); - renderBoard(); - FastLED.show(); - if (scanBoard(aiP)) + int8_t aiPlayer = (menuMode == 0) ? 2 : 1; + performAiMove(aiPlayer); + winnerPlayer = scanBoard(); + if (winnerPlayer != 0) { - currentPlayer = aiP; gameState = FINISHED_WIN; + demoResetTimer = millis(); } else if (isBoardFull()) + { gameState = FINISHED_DRAW; + demoResetTimer = millis(); + } } else { @@ -456,21 +553,19 @@ void loop() } else if (gameState == DEMO) { - // No idle timeout check here to prevent premature restarts renderBoard(); FastLED.show(); delay(600); performAiMove(currentPlayer); - if (scanBoard(currentPlayer)) + winnerPlayer = scanBoard(); + if (winnerPlayer != 0) { gameState = FINISHED_WIN; - isDemoOver = true; demoResetTimer = millis(); } else if (isBoardFull()) { gameState = FINISHED_DRAW; - isDemoOver = true; demoResetTimer = millis(); } else @@ -479,16 +574,7 @@ void loop() } } else - { - // Monitor for Idle in Win screen to return to Demo - if (!isDemoOver && (millis() - lastActivityTime > current_idle_timeout_ms)) - { - memset(board, 0, sizeof(board)); - gameState = DEMO; - currentPlayer = 1; - return; - } - + { // FINISHED state static uint32_t lastFlash = 0; static bool toggle = true; if (millis() - lastFlash > 300) @@ -503,9 +589,9 @@ void loop() if (gameState == FINISHED_WIN) { if (winMask[i]) - leds[i] = toggle ? (currentPlayer == 1 ? CRGB::Yellow : CRGB::Red) : CRGB::Black; + leds[i] = toggle ? (winnerPlayer == 1 ? CRGB::Yellow : CRGB::Red) : CRGB::Black; else - leds[i].nscale8(40); + leds[i].nscale8(60); } else if (gameState == FINISHED_DRAW) { @@ -515,12 +601,12 @@ void loop() } FastLED.show(); } - // Restart Demo loop if it was a demo game - if (isDemoOver && (millis() - demoResetTimer > 30000)) + if (millis() - demoResetTimer > 15000) { memset(board, 0, sizeof(board)); gameState = DEMO; - isDemoOver = false; + demoResetTimer = 0; + demoPly = random(3, 7); } if (pressed) { diff --git a/uv.lock b/uv.lock deleted file mode 100644 index d603d37..0000000 --- a/uv.lock +++ /dev/null @@ -1,302 +0,0 @@ -version = 1 -revision = 3 -requires-python = ">=3.14" - -[[package]] -name = "bitarray" -version = "3.8.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/95/06/92fdc84448d324ab8434b78e65caf4fb4c6c90b4f8ad9bdd4c8021bfaf1e/bitarray-3.8.0.tar.gz", hash = "sha256:3eae38daffd77c9621ae80c16932eea3fb3a4af141fb7cc724d4ad93eff9210d", size = 151991, upload-time = "2025-11-02T21:41:15.117Z" } -wheels = [ - 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