How does reinforcement learning through self-play contribute to the development of superhuman AI performance in classic games?
Tuesday, 11 June 2024
by EITCA Academy
Reinforcement learning (RL) through self-play has been a pivotal methodology in achieving superhuman performance in classic games. This approach, rooted in the principles of trial and error and reward maximization, allows an artificial agent to learn optimal strategies by playing against itself. Unlike traditional supervised learning, where an algorithm learns from a labeled dataset, reinforcement
What is the significance of the discount factor ( gamma ) in the context of reinforcement learning, and how does it influence the training and performance of a DRL agent?
Tuesday, 11 June 2024
by EITCA Academy
The discount factor, denoted as , is a fundamental parameter in the context of reinforcement learning (RL) that significantly influences the training and performance of a deep reinforcement learning (DRL) agent. The discount factor is a scalar value between 0 and 1, inclusive, and it serves a critical role in determining the present value of