Algorithms-For-Agent

A personal study and development workspace for algorithms useful for Agent and game demos, tailored to Digital Media Technology (DMT) students.

Project Overview

This repository collects algorithm problems, clean Python implementations, and minimal unit tests focused on the algorithms most relevant to building intelligent agents, game AI, and interactive media demos.

Repository Structure

.
├── README.md                  # This file
├── LEARNING_PLAN.md           # Detailed weekly learning plan
├── CONTRIBUTING.md            # Contribution and commit style guide
├── requirements.txt           # Python dependencies
├── LICENSE                    # MIT License
├── .gitignore                 # Python gitignore
├── .pre-commit-config.yaml    # black + flake8 hooks
├── templates/
│   ├── problem-template.md    # Template for new problem write-ups
│   └── solution-template.py   # Template for new Python solutions
├── docs/
│   └── complexity.md          # Quick-reference complexity cheat-sheet
├── agent_tasks/
│   └── README.md              # Agent framework interfaces & task backlog
├── problems/
│   ├── index.md               # Master index of all problems
│   └── agents/                # Agent-focused algorithm problems
│       ├── 0001-a_star.md
│       ├── 0002-bfs-grid.md
│       ├── 0003-dijkstra.md
│       ├── 0004-priority-queue.md
│       └── 0005-minimax-tictactoe.md
├── implementations/
│   └── python/                # Python implementations
│       ├── 0001_a_star.py
│       ├── 0002_bfs_grid.py
│       ├── 0003_dijkstra.py
│       ├── 0004_priority_queue.py
│       └── 0005_minimax.py
├── tests/                     # pytest unit tests
│   ├── test_0001_a_star.py
│   ├── test_0002_bfs_grid.py
│   ├── test_0003_dijkstra.py
│   ├── test_0004_priority_queue.py
│   └── test_0005_minimax.py
└── algorithms/                # Legacy study notes and examples

How to Run Tests

# Create and activate a virtual environment
python -m venv .venv
source .venv/bin/activate        # Windows: .\.venv\Scripts\Activate.ps1

# Install dependencies
pip install -r requirements.txt

# Run all tests
pytest -q

# Run a specific test file
pytest tests/test_0001_a_star.py -q

Usage

1. Browse problems/agents/ and read the .md file for the problem statement, examples, and approach.
2. Study or extend the matching implementation under implementations/python/.
3. Run the tests with pytest to verify correctness.
4. Use templates/problem-template.md and templates/solution-template.py when adding new problems.
5. See LEARNING_PLAN.md for the suggested weekly study schedule.

Contributing

See CONTRIBUTING.md for commit style and contribution guidelines.