What is an Accumulating Eligibility Trace?
An Accumulating Eligibility Trace is a type of eligibility trace, which is a method used in reinforcement learning to keep track of which actions and states are responsible for rewards or punishments. This trace is accumulative in nature, meaning it increments over time, and is used to update the value function of the agent.
Eligibility traces are used in reinforcement learning to keep track of the history of actions and states that led to a certain r
Dutch Eligibility Trace Overview
When training a machine learning model, it's important to keep track of which features or inputs are contributing to the output. This is where eligibility traces come in. An eligibility trace is a method used in reinforcement learning algorithms to update the weights of a neural network based on which inputs are most influential.
The Dutch Eligibility Trace is one particular type of eligibility trace. It's based on the classic eligibility trace formula, but wit
An eligibility trace is a tool utilized in reinforcement learning to assist with the challenge of credit assignment. Credit assignment is the task of determining which past actions should receive credit or blame for a current outcome. Eligibility traces help to solve this problem by storing recent actions that contribute to the outcome.
Memory Vector
An eligibility trace is represented as a memory vector $\textbf{z}\_{t}$ that is parallel to the long-term weight vector $\textbf{w}\_{t}$. The
Understanding Replacing Eligibility Trace in Reinforcement Learning
Reinforcement learning is a type of machine learning where an algorithm is trained to learn the optimal behavior in a specific environment. One of the key elements of reinforcement learning is the concept of eligibility traces. Eligibility traces are used to update the value function of an agent in a way that takes into account not only the current reward but also the recent history of the agent's actions.
Among the various ty