Browsing: Reward Function

The use of reinforcement learning from human feedback (RLHF) in AI training is not as effective as true reinforcement learning, as it relies on…

This article looks back at some of the excellent blog posts from contributors in 2023. It covers topics such as neurosymbolic approaches for reasoning…

WiMi Hologram Cloud Inc. has developed a deep reinforcement learning-based task scheduling algorithm in cloud computing to improve the performance and resource utilization of…

Reward function value decomposition is a method used in reinforcement learning to decompose a composite reward into its individual components. This allows the Agent…

In our recent AAAI 2023 paper, Misspecification in Inverse Reinforcement Learning, we study the question of how robust the inverse reinforcement learning problem is…

Interaction-Grounded Learning (IGL) is a new paradigm that allows agents to infer reward functions from arbitrary feedback signals instead of explicit numeric rewards. This…