Using Reinforcement Learning in Unity Environments for Training AI Agent
Geetika Munjal, Monika Lamba · 2024
An intelligent AI agent capable of performing tasks in a virtual environment is developed using reinforcement learning techniques. This chapter serves to demonstrate how machine learning and artificial intelligence methods can be employed to deploy an AI agent across settings, effectively addressing a wide range of challenges. By utilizing an AI agent, the need for developing agents for each unique problem encountered in diverse environments is eliminated. This approach transforms the AI agent into an entity that can be trained and adapted to scenarios, enabling it to effectively solve specific problems presented in each situation. The utilization of AI agents enhances resilience and adaptability in dynamic environments, leading to optimized resource allocation (including time, money, and energy) and increased human innovation. To accomplish this, the tools utilized are Unity 3D Engine, Python programming language, PyTorch framework, and ML agents.