Reinforcement Learning for Autonomous Agents

Thesis Abstract

This project focuses on the application of reinforcement learning techniques to train autonomous agents for decision-making in complex environments. The research will explore various reinforcement learning algorithms and their suitability for training agents to perform tasks such as navigation, control, and optimization. The project aims to investigate the effectiveness of reinforcement learning in enabling autonomous agents to adapt to dynamic and uncertain environments.