feat(tic-tac-toe): Tic-Tac-Toe AI agent by Liam Soulet

topics/tic-tac-toe/Cargo.toml

@@ -0,0 +1,6 @@
+[package]
+name = "tic-tac-toe"
+version = "0.1.0"
+edition = "2024"
+
+[dependencies]

topics/tic-tac-toe/docs/architecture.md

@@ -0,0 +1,221 @@
+# Tic-Tac-Toe AI Agent - Architecture Document
+
+## Project Definition
+
+This project implements a command-line Tic-Tac-Toe game where a human player competes against an AI opponent. The AI uses the Minimax algorithm with depth-first search to play optimally, ensuring it never loses and will either win or draw every game.
+
+### Goals
+- Create an interactive command-line Tic-Tac-Toe game
+- Implement an unbeatable AI using the Minimax algorithm
+- Provide a clean, modular architecture with clear separation of concerns
+- Ensure the code is well-documented, tested, and follows Rust best practices
+- Build a system that can be easily extended or modified
+
+## Components and Modules
+
+The project is architected using a layered, modular approach with clear separation of responsibilities:
+
+### Core Modules
+
+#### 1. **Board Module (`board.rs`)**
+**Responsibility**: Physical game state representation and basic operations
+- Represents the 3x3 game board as a 1D array for efficiency
+- Manages cell states (Empty, Occupied by Player X/O)
+- Handles move placement and position validation
+- Provides board querying methods (empty positions, full board check)
+- Implements clean display formatting
+
+#### 2. **Game Module (`game.rs`)**
+**Responsibility**: Game logic, rules, and state management
+- Manages overall game state (InProgress, Won, Draw)
+- Handles player turns and move validation
+- Implements win condition detection using pattern matching
+- Provides game flow control (reset, state transitions)
+- Acts as the central coordinator between other modules
+
+#### 3. **AI Module (`ai.rs`)**
+**Responsibility**: Intelligent opponent using Minimax algorithm
+- Implements the Minimax algorithm with depth-first search
+- Evaluates all possible game states recursively
+- Scores positions: +10 for AI win, -10 for AI loss, 0 for draw
+- Optimizes for winning quickly and losing slowly
+- Provides unbeatable gameplay that never loses
+
+#### 4. **UI Module (`ui.rs`)**
+**Responsibility**: User interaction and interface management
+- Handles command-line input/output operations
+- Manages game flow (start, play rounds, restart)
+- Provides user-friendly error messages and feedback
+- Displays board state and position guides
+- Coordinates between human input and AI responses
+
+#### 5. **Main Application (`main.rs`)**
+**Responsibility**: Entry point and module coordination
+- Orchestrates all modules
+- Initializes the game system
+- Provides the main execution flow
+
+### Architecture Justification
+
+This modular design follows several key principles:
+
+**1. Single Responsibility Principle**: Each module has one clear purpose
+- Board: Data representation
+- Game: Business logic
+- AI: Intelligence algorithms  
+- UI: User interaction
+
+**2. Separation of Concerns**: Clear boundaries between layers
+- Data layer (Board) is independent of game rules
+- Game logic is separate from AI implementation
+- UI is decoupled from core game mechanics
+
+**3. Dependency Direction**: Clean dependency flow
+```
+main.rs → ui.rs → game.rs → board.rs
+       → ai.rs ↗
+```
+
+**4. Testability**: Each module can be unit tested independently
+- 11 tests for Board operations
+- 14 tests for Game logic  
+- 6 tests for AI behavior
+- 4 integration tests for UI
+
+**5. Extensibility**: Easy to modify or extend
+- AI algorithm can be swapped without affecting other modules
+- UI can be replaced (web, GUI) without changing core logic
+- Game rules can be modified independently
+
+## Usage
+
+### Building and Running
+
+```bash
+# Navigate to project directory
+cd topics/tic-tac-toe
+
+# Build the project
+cargo build
+
+# Run the game
+cargo run
+
+# Run tests
+cargo test
+```
+
+### Gameplay Experience
+
+#### 1. **Game Start**
+The game displays a welcome message and position guide:
+```
+🎮 Welcome to Tic-Tac-Toe! 🎮
+You are X, AI is O.
+Enter positions 1-9 corresponding to board positions:
+
+Board positions:
+ 1 | 2 | 3 
+-----------
+ 4 | 5 | 6 
+-----------
+ 7 | 8 | 9 
+```
+
+#### 2. **Gameplay Flow**
+- Human player (X) always goes first
+- Enter positions 1-9 to place your mark
+- AI automatically responds with optimal moves
+- Game displays board state after each move
+- Clear feedback for invalid moves or occupied positions
+
+#### 3. **Example Game Session**
+```
+🆕 Starting new game!
+
+   |   |   
+-----------
+   |   |   
+-----------
+   |   |   
+
+Your move (1-9): 5
+
+   |   |   
+-----------
+   | X |   
+-----------
+   |   |   
+
+🤖 AI is thinking...
+🤖 AI plays position 1
+
+ O |   |   
+-----------
+   | X |   
+-----------
+   |   |   
+
+Your move (1-9): 9
+```
+
+#### 4. **Game Results**
+The game automatically detects and displays results:
+- **Human Win**: "🎉 Congratulations! Player X wins! 🎉"
+- **AI Win**: "🎉 Congratulations! Player O wins! 🎉"  
+- **Draw**: "🤝 It's a draw! Well played both players! 🤝"
+
+#### 5. **Replay Option**
+After each game, players can choose to play again:
+```
+🔄 Would you like to play again? (y/n): y
+```
+
+### AI Behavior
+
+The AI implements optimal Minimax strategy:
+- **Defensive**: Automatically blocks human winning moves
+- **Offensive**: Takes immediate winning opportunities
+- **Strategic**: Chooses moves that maximize long-term advantage
+- **Unbeatable**: Mathematical guarantee of never losing
+
+### Development and Testing
+
+#### Running Tests
+```bash
+# Run all tests (35 total)
+cargo test
+
+# Run specific module tests
+cargo test board::tests
+cargo test game::tests  
+cargo test ai::tests
+cargo test ui::tests
+
+# Run with verbose output
+cargo test -- --nocapture
+```
+
+#### Code Quality
+```bash
+# Check for compilation issues
+cargo check
+
+# Format code
+cargo fmt
+
+# Run clippy for additional lints
+cargo clippy
+```
+
+### Technical Specifications
+
+- **Language**: Rust (Edition 2024)
+- **Dependencies**: Standard library only
+- **Board Representation**: 1D array of 9 positions
+- **AI Algorithm**: Minimax with depth-first search
+- **Input Validation**: Comprehensive error handling
+- **Test Coverage**: 35 unit and integration tests
+- **Performance**: Instant AI response for all game states
+
+This architecture provides a robust, maintainable, and extensible foundation for the Tic-Tac-Toe game while demonstrating clean code principles and effective modular design.