Ants Saga Laboratory
Learn Reinforcement Learning from scratch: from creating the environment in Unity to training agents with Q-Learning
AvailableIntermediate8-12 hours
Project Overview
Ants Saga is our first complete educational project that takes you from creating a simulation environment in Unity to training intelligent agents with Reinforcement Learning. Follow our unique Hub-and-Spoke model to master both game development and AI.
The Challenge
Train ants to learn how to collect food while avoiding obstacles and predators. This seemingly simple task involves complex decision-making, exploration, and optimization - perfect for understanding RL concepts.
Laboratory Sections
Proto Lab - Unity GameDev
Create the environment from scratch in Unity
Beginner4-6 hours
UnityC#Game DevelopmentSimulation
RL Lab - Q-Learning Python
Train intelligent agents using Q-Learning
Intermediate4-6 hours
PythonQ-LearningMachine LearningAI
Project Preview
See the complete project in action with trained agents navigating the environment.
Learning Objectives
- Understand the fundamentals of Reinforcement Learning
- Create a complete simulation environment in Unity
- Implement Q-Learning algorithm from scratch
- Train agents to solve complex navigation problems
- Analyze and optimize agent performance
Prerequisites
- Basic programming knowledge (Python/C#)
- Unity 2022.3 LTS installed
- Python 3.8+ with required libraries
- Motivation to learn hands-on