TD3-BST: A Machine Learning Algorithm to Adjust the Strength of Regularization Dynamically Using Uncertainty Model

Reinforcement learning (RL) is a type of learning approach where an agent interacts with an environment to collect experiences and aims to maximize the reward received from the environment. This usually involves a looping process of experience collecting and enhancement, and due to the requirement of policy rollouts, it is called online RL. Both on-policy […]

The post TD3-BST: A Machine Learning Algorithm to Adjust the Strength of Regularization Dynamically Using Uncertainty Model appeared first on MarkTechPost.

agent ai paper summary ai shorts algorithm applications artificial intelligence editors pick environment experience machine machine learning process regularization reinforcement reinforcement learning staff tech news technology the environment type uncertainty