A General Perspective on Objectives of Reinforcement Learning

2023/06/05 by Yang Long, Yang, Long
Biochemistry, Genetics and Molecular Biology · Computer Science · #Evolutionary Algorithms and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Reinforcement Learning in Robotics #Viral Infectious Diseases and Gene Expression in Insects

paper · pdf · doi:10.48550/arxiv.2306.03074

openalex publication_date 2023/06/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this lecture, we present a general perspective on reinforcement learning (RL) objectives, where we show three versions of objectives. The first version is the standard definition of objective in RL literature. Then we extend the standard definition to the λ-return version, which unifies the standard definition of objective. Finally, we propose a general objective that unifies the previous two versions. The last version provides a high level to understand of RL's objective, where it shows a fundamental formulation that connects some widely used RL techniques (e.g., TD(λ) and GAE), and this objective can be potentially applied to extensive RL algorithms.

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