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?
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
What is the Bellman equation, and how is it used in the context of Temporal Difference (TD) learning and Q-learning?
The Bellman equation, named after Richard Bellman, is a fundamental concept in the field of reinforcement learning (RL) and dynamic programming. It provides a recursive decomposition for solving the problem of finding an optimal policy. The Bellman equation is central to various RL algorithms, including Temporal Difference (TD) learning and Q-learning, which are pivotal in
What is the main advantage of model-free reinforcement learning methods compared to model-based methods?
Model-free reinforcement learning (RL) methods have gained significant attention in the field of artificial intelligence due to their unique advantages over model-based methods. The primary advantage of model-free methods lies in their ability to learn optimal policies and value functions without requiring an explicit model of the environment. This characteristic provides several benefits, including reduced