Speaker
Mr
Radu Ciobanu
(West University of Timisoara)
Description
Reinforcement Learning (RL) stands as a fundamental approach for optimization problems, characterized by an iterative experimentation to maximize the cumulative reward of an agent performing in its environment. This paper highlights how game engines serve as the perfect training environments for intelligent agents, leveraging state-of-the-art RL algorithms.
Primary author
Mr
Radu Ciobanu
(West University of Timisoara)
Co-author
Dr
Daniela Zaharie
(West University of Timisoara)
