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
How does the Bellman equation facilitate the process of policy evaluation in dynamic programming, and what role does the discount factor play in this context?
The Bellman equation is a cornerstone in the field of dynamic programming and plays a pivotal role in the evaluation of policies within the framework of Markov Decision Processes (MDPs). In the context of reinforcement learning, the Bellman equation provides a recursive decomposition that simplifies the process of determining the value of a policy. This
How are the policy gradients used?
Policy gradient methods are a class of algorithms in reinforcement learning that optimize the policy directly. In reinforcement learning, a policy is a mapping from states of the environment to actions to be taken when in those states. The objective of policy gradient methods is to find the optimal policy that maximizes the expected cumulative