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[update] Progressive difficulty, demo fixes, and background docs.

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Seppe De Loore
2026-03-06 22:14:25 +01:00
parent 8a776dfae5
commit da63f05ac3
7 changed files with 414 additions and 575 deletions
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.gitignore
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.vscode/c_cpp_properties.json .vscode/c_cpp_properties.json
.vscode/launch.json .vscode/launch.json
.vscode/ipch .vscode/ipch
.vscode/settings.json
.vscode/settings.json
Vendored
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@@ -1,9 +0,0 @@
{
"cSpell.words": [
"espressif",
"fastled",
"lolin",
"microcontroller",
"paulstoffregen"
]
}
Background information.md
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# 📑 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)
README.md
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# Connect Four: ESP32-C3 LED Edition # 🕹️ 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. 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.
## 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]`
--- ---
## 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**. ### 📐 Physical Layout
It explores a "tree" of possibilities: _"If I play here, and the player plays there, then I can play here..."_
### 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**. - **Row 0:** Interaction & AI Decision Visualization.
This allows the AI to "prune" (ignore) branches of the game tree that are mathematically - **Row 1:** Static Blue UI border.
guaranteed to be worse than moves it has already found, significantly speeding up the calculation. - **Rows 2-7:** Active $7 \times 6$ game board.
- **Status Column:** Far right column (Index 7) manages UI framing and "Glow" effects.
### 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.
--- ---
## Technical Specifications ## 🧠 Advanced AI & Logic Features
### Hardware Pins (Lolin C3 Mini) ### 1. Progressive Difficulty (Evolution Mode)
| Component | Pin | Function | To keep the game challenging and the CPU efficient, the AI search depth (Ply) scales as the board fills.
| :---------- | :-- | :--------------------------------------- |
| **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) |
### 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). The win-engine has been refactored to prevent "color ghosting."
- **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." - **Winner Locking:** The `scanBoard()` function returns the specific ID of the winner (1 for Yellow, 2 for Red).
- **Glowing Frame**: During Demo mode, the blue borders pulse with a white "glow" effect using a `beat8` sine wave to indicate autonomous play. - **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. ### 🔄 State Machine
- **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.
## 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. ### 🌐 Web Administration Portal
- `DEMO_RESET_PAUSE`: Delay (ms) between games in Demo Mode.
- `DEBOUNCE_DELAY`: Sensitivity of the encoder button. Accessible via the **"Connect4-Config"** AP at `192.168.4.1`.
- `BRIGHTNESS`: Global brightness of the NeoPixels.
- **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.
app.db
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src/main.cpp
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@@ -9,6 +9,7 @@
const int COLS = 7; const int COLS = 7;
const int ROWS = 6; const int ROWS = 6;
// --- Configuration & Globals ---
CRGB leds[NUM_LEDS]; CRGB leds[NUM_LEDS];
Encoder myEnc(ENC_A, ENC_B); Encoder myEnc(ENC_A, ENC_B);
WebServer server(80); WebServer server(80);
@@ -28,52 +29,47 @@ State gameState = MENU;
int8_t menuMode = 0; int8_t menuMode = 0;
int8_t currentPlayer = 1; int8_t currentPlayer = 1;
int8_t winnerPlayer = 0; // Tracks who actually won for the flashing effect
int8_t activeCol = 3; int8_t activeCol = 3;
long oldEncPos = -999; long oldEncPos = -999;
uint32_t lastActivityTime = 0; uint32_t lastActivityTime = 0;
uint32_t demoResetTimer = 0; uint32_t demoResetTimer = 0;
bool isDemoOver = false; bool isDemoOver = false;
uint8_t demoPly = 4;
// Web-Configurable Parameters (Stored in Flash)
uint8_t current_look_ahead; uint8_t current_look_ahead;
uint8_t current_brightness; uint8_t current_brightness;
uint32_t current_idle_timeout_ms; uint32_t current_idle_timeout_ms;
bool blunder_enabled = false;
bool progressive_difficulty = false;
// Thinking Animation Helpers
uint8_t aiBrightness = 0; uint8_t aiBrightness = 0;
bool aiFadeUp = true; bool aiFadeUp = true;
// --- Helper Functions --- // --- Function Prototypes ---
int getIdx(int x, int y) { return (y * 8) + x; } 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) // --- Utility & Rendering ---
{
static uint32_t lastCycle = 0; int getIdx(int x, int y) { return (y * 8) + x; }
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();
}
void drawStaticUI() void drawStaticUI()
{ {
FastLED.clear(); FastLED.clear();
CRGB borderColor = CRGB::Blue; CRGB borderColor = CRGB::Blue;
if (gameState == DEMO || (gameState >= 2 && isDemoOver)) if (gameState == DEMO || gameState >= 2)
{ {
uint8_t glow = beat8(15); uint8_t glow = beat8(15);
borderColor = blend(CRGB::Blue, CRGB::White, glow / 4); borderColor = blend(CRGB::Blue, CRGB::White, glow / 4);
@@ -109,6 +105,80 @@ int getFirstEmptyRow(int col)
return -1; 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() bool isBoardFull()
{ {
for (int c = 0; c < COLS; c++) for (int c = 0; c < COLS; c++)
@@ -117,74 +187,85 @@ bool isBoardFull()
return true; return true;
} }
bool scanBoard(int8_t p) int8_t scanBoard()
{ {
memset(winMask, 0, sizeof(winMask)); memset(winMask, 0, sizeof(winMask));
bool found = false; auto check = [&](int column, int row, int columnOffset, int rowOffset)
auto check = [&](int c, int r, int dc, int dr)
{ {
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++) for (int index = 0; index < 4; index++)
winMask[getIdx(c + i * dc, 7 - (r + i * dr))] = true; winMask[getIdx(column + index * columnOffset, 7 - (row + index * rowOffset))] = true;
return true; return postion;
} }
return false; return (int8_t)0;
}; };
for (int r = 0; r < 6; r++) for (int row = 0; row < 6; row++)
for (int c = 0; c < 4; c++) for (int column = 0; column < 4; column++)
if (check(c, r, 1, 0)) {
found = true; int8_t res = check(column, row, 1, 0);
for (int r = 0; r < 3; r++) if (res)
for (int c = 0; c < 7; c++) return res;
if (check(c, r, 0, 1)) }
found = true; for (int row = 0; row < 3; row++)
for (int r = 0; r < 3; r++) for (int column = 0; column < 7; column++)
for (int c = 0; c < 4; c++) {
if (check(c, r, 1, 1)) int8_t res = check(column, row, 0, 1);
found = true; if (res)
for (int r = 3; r < 6; r++) return res;
for (int c = 0; c < 4; c++) }
if (check(c, r, 1, -1)) for (int row = 0; row < 3; row++)
found = true; for (int column = 0; column < 4; column++)
return found; {
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 aiPlayer, int8_t humanPlayer, int8_t rootCol)
int minimax(int depth, int alpha, int beta, bool isMax, int8_t aiP, int8_t huP)
{ {
if (depth >= current_look_ahead - 1) if (depth >= current_look_ahead - 1)
updateThinkingLED(aiP); updateThinkingVisuals(aiPlayer, rootCol);
else else
yield(); yield();
if (scanBoard(aiP)) // Check for wins within minimax
int8_t win = scanBoard();
if (win == aiPlayer)
return 1000 + depth; return 1000 + depth;
if (scanBoard(huP)) if (win == humanPlayer)
return -1000 - depth; return -1000 - depth;
if (depth == 0 || isBoardFull()) if (depth == 0 || isBoardFull())
return 0; return 0;
int order[] = {3, 2, 4, 1, 5, 0, 6}; int order[] = {3, 2, 4, 1, 5, 0, 6};
int best = isMax ? -2000 : 2000; int best = isMax ? -2000 : 2000;
for (int c : order) for (int column : order)
{ {
int r = getFirstEmptyRow(c); int row = getFirstEmptyRow(column);
if (r != -1) if (row != -1)
{ {
board[c][r] = isMax ? aiP : huP; board[column][row] = isMax ? aiPlayer : humanPlayer;
int val = minimax(depth - 1, alpha, beta, !isMax, aiP, huP); int val = minimax(depth - 1, alpha, beta, !isMax, aiPlayer, humanPlayer, (depth == current_look_ahead ? column : rootCol));
board[c][r] = 0; board[column][row] = 0;
if (isMax) if (isMax)
{ {
if (val > best) best = max(best, val);
best = val;
alpha = max(alpha, best); alpha = max(alpha, best);
} }
else else
{ {
if (val < best) best = min(best, val);
best = val;
beta = min(beta, best); beta = min(beta, best);
} }
if (beta <= alpha) 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; return best;
} }
void performAiMove(int8_t aiP) void performAiMove(int8_t aiPlayer)
{ {
int8_t huP = (aiP == 1) ? 2 : 1; int humanPlayer = (aiPlayer == 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 bestScore = -30000; int bestScore = -30000;
int bestCol = 3; 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); int row = getFirstEmptyRow(column);
if (r != -1) if (row != -1)
{ {
board[c][r] = aiP; board[column][row] = aiPlayer;
int score = minimax(current_look_ahead, -30000, 30000, false, aiP, huP); if (scanBoard() == aiPlayer)
board[c][r] = 0; {
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) if (score > bestScore)
{ {
bestScore = score; bestScore = score;
bestCol = c; bestCol = column;
} }
} }
} }
board[bestCol][getFirstEmptyRow(bestCol)] = aiP; if ((gameState == DEMO || blunder_enabled) && random(100) < 20)
leds[getIdx(7, 0)] = CRGB::Black; {
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><head><meta name='viewport' content='width=device-width, initial-scale=1'>"
"<style>body{font-family:sans-serif;background:#121212;color:white;text-align:center;}"
" .card{background:#222;padding:25px;border-radius:15px;display:inline-block;margin-top:20px;}"
" input{width:100%;padding:10px;margin:10px 0;border-radius:5px;border:none;}</style></head><body>";
html += "<h1>Connect 4 Admin</h1><div class='card'><form action='/save' method='POST'>";
html += "Base AI Ply (1-10):<input type='number' name='ply' value='" + String(current_look_ahead) + "'>";
html += "Brightness (5-255):<input type='number' name='br' value='" + String(current_brightness) + "'>";
html += "Idle Timeout (Sec):<input type='number' name='idle' value='" + String(current_idle_timeout_ms / 1000) + "'>";
html += "Enable Blunders: <input type='checkbox' name='blunder' " + String(blunder_enabled ? "checked" : "") + "><br>";
html += "Evolution Mode: <input type='checkbox' name='evolve' " + String(progressive_difficulty ? "checked" : "") + "><br><br>";
html += "<input type='submit' value='Save Settings' style='background:#28a745;color:white;font-weight:bold;'></form></div></body></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() void showMenu()
{ {
isDemoOver = false; isDemoOver = false;
@@ -279,42 +415,6 @@ void showMenu()
FastLED.show(); FastLED.show();
} }
// --- Web Portal ---
void handleRoot()
{
String html = "<html><head><meta name='viewport' content='width=device-width, initial-scale=1'>";
html += "<style>body{font-family:sans-serif;background:#121212;color:white;text-align:center;} .card{background:#222;padding:25px;border-radius:15px;display:inline-block;margin-top:20px;} input{width:100%;padding:10px;margin:10px 0;border-radius:5px;border:none;}</style></head><body>";
html += "<h1>Connect 4 Admin</h1><div class='card'><form action='/save' method='POST'>";
html += "AI Ply (1-10):<input type='number' name='ply' value='" + String(current_look_ahead) + "'>";
html += "Brightness (5-255):<input type='number' name='br' value='" + String(current_brightness) + "'>";
html += "Idle Timeout (Sec):<input type='number' name='idle' value='" + String(current_idle_timeout_ms / 1000) + "'>";
html += "<input type='submit' value='Save Settings' style='background:#28a745;color:white;font-weight:bold;'></form></div></body></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() void setup()
{ {
Serial.begin(115200); Serial.begin(115200);
@@ -322,29 +422,16 @@ void setup()
current_look_ahead = prefs.getUChar("ply", 8); current_look_ahead = prefs.getUChar("ply", 8);
current_brightness = prefs.getUChar("br", 25); current_brightness = prefs.getUChar("br", 25);
current_idle_timeout_ms = prefs.getUInt("idle", 60) * 1000; current_idle_timeout_ms = prefs.getUInt("idle", 60) * 1000;
blunder_enabled = prefs.getBool("blunder", false);
progressive_difficulty = prefs.getBool("evolve", false);
FastLED.addLeds<WS2812B, LED_PIN, GRB>(leds, NUM_LEDS); FastLED.addLeds<WS2812B, LED_PIN, GRB>(leds, NUM_LEDS);
FastLED.setBrightness(current_brightness); FastLED.setBrightness(current_brightness);
pinMode(ENC_SW, INPUT_PULLUP); pinMode(ENC_SW, INPUT_PULLUP);
WiFi.softAP("Connect4-Config", WIFI_PASSWORD);
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!");
}
server.on("/", handleRoot); server.on("/", handleRoot);
server.on("/save", HTTP_POST, handleSave); server.on("/save", HTTP_POST, handleSave);
server.begin(); server.begin();
lastActivityTime = millis(); lastActivityTime = millis();
showMenu(); showMenu();
} }
@@ -355,18 +442,17 @@ void loop()
long newPos = myEnc.read() / SENSITIVITY; long newPos = myEnc.read() / SENSITIVITY;
bool pressed = (digitalRead(ENC_SW) == LOW); bool pressed = (digitalRead(ENC_SW) == LOW);
// Escape Demo / Interrupt
if (newPos != oldEncPos || (pressed && (millis() - lastActivityTime > 500))) 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); fadeToBlackBy(leds, NUM_LEDS, 32);
FastLED.show(); FastLED.show();
delay(30); delay(30);
} }
delay(2000); delay(500);
gameState = MENU; gameState = MENU;
memset(board, 0, sizeof(board)); memset(board, 0, sizeof(board));
showMenu(); showMenu();
@@ -377,6 +463,16 @@ void loop()
lastActivityTime = millis(); 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 (gameState == MENU)
{ {
if (newPos != oldEncPos) if (newPos != oldEncPos)
@@ -400,12 +496,6 @@ void loop()
} }
delay(300); delay(300);
} }
if (millis() - lastActivityTime > current_idle_timeout_ms)
{
gameState = DEMO;
memset(board, 0, sizeof(board));
currentPlayer = 1;
}
} }
else if (gameState == PLAYING) else if (gameState == PLAYING)
{ {
@@ -422,28 +512,35 @@ void loop()
int row = getFirstEmptyRow(activeCol); int row = getFirstEmptyRow(activeCol);
if (row != -1) if (row != -1)
{ {
board[activeCol][row] = currentPlayer; animateDrop(activeCol, currentPlayer);
renderBoard(); winnerPlayer = scanBoard();
FastLED.show(); if (winnerPlayer != 0)
if (scanBoard(currentPlayer)) {
gameState = FINISHED_WIN; gameState = FINISHED_WIN;
demoResetTimer = millis();
}
else if (isBoardFull()) else if (isBoardFull())
{
gameState = FINISHED_DRAW; gameState = FINISHED_DRAW;
demoResetTimer = millis();
}
else else
{ {
if (menuMode < 2) if (menuMode < 2)
{ {
int8_t aiP = (menuMode == 0) ? 2 : 1; int8_t aiPlayer = (menuMode == 0) ? 2 : 1;
performAiMove(aiP); performAiMove(aiPlayer);
renderBoard(); winnerPlayer = scanBoard();
FastLED.show(); if (winnerPlayer != 0)
if (scanBoard(aiP))
{ {
currentPlayer = aiP;
gameState = FINISHED_WIN; gameState = FINISHED_WIN;
demoResetTimer = millis();
} }
else if (isBoardFull()) else if (isBoardFull())
{
gameState = FINISHED_DRAW; gameState = FINISHED_DRAW;
demoResetTimer = millis();
}
} }
else else
{ {
@@ -456,21 +553,19 @@ void loop()
} }
else if (gameState == DEMO) else if (gameState == DEMO)
{ {
// No idle timeout check here to prevent premature restarts
renderBoard(); renderBoard();
FastLED.show(); FastLED.show();
delay(600); delay(600);
performAiMove(currentPlayer); performAiMove(currentPlayer);
if (scanBoard(currentPlayer)) winnerPlayer = scanBoard();
if (winnerPlayer != 0)
{ {
gameState = FINISHED_WIN; gameState = FINISHED_WIN;
isDemoOver = true;
demoResetTimer = millis(); demoResetTimer = millis();
} }
else if (isBoardFull()) else if (isBoardFull())
{ {
gameState = FINISHED_DRAW; gameState = FINISHED_DRAW;
isDemoOver = true;
demoResetTimer = millis(); demoResetTimer = millis();
} }
else else
@@ -479,16 +574,7 @@ void loop()
} }
} }
else else
{ { // FINISHED state
// 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;
}
static uint32_t lastFlash = 0; static uint32_t lastFlash = 0;
static bool toggle = true; static bool toggle = true;
if (millis() - lastFlash > 300) if (millis() - lastFlash > 300)
@@ -503,9 +589,9 @@ void loop()
if (gameState == FINISHED_WIN) if (gameState == FINISHED_WIN)
{ {
if (winMask[i]) 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 else
leds[i].nscale8(40); leds[i].nscale8(60);
} }
else if (gameState == FINISHED_DRAW) else if (gameState == FINISHED_DRAW)
{ {
@@ -515,12 +601,12 @@ void loop()
} }
FastLED.show(); FastLED.show();
} }
// Restart Demo loop if it was a demo game if (millis() - demoResetTimer > 15000)
if (isDemoOver && (millis() - demoResetTimer > 30000))
{ {
memset(board, 0, sizeof(board)); memset(board, 0, sizeof(board));
gameState = DEMO; gameState = DEMO;
isDemoOver = false; demoResetTimer = 0;
demoPly = random(3, 7);
} }
if (pressed) if (pressed)
{ {
uv.lock
Generated
-302
View File
@@ -1,302 +0,0 @@
version = 1
revision = 3
requires-python = ">=3.14"
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