Work

Toward General Function Approximation in Nonstationary Reinforcement Learning

Year: 2024

Type: article

Source: IEEE Journal on Selected Areas in Information Theory

DOI: 10.1109/jsait.2024.3381818

Authors: Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang

Institutions: University of Florida, Princeton University, Pennsylvania State University, University of California, Santa Barbara, The Ohio State University

Language: English

Topic: Reinforcement Learning in Robotics

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

Funder: National Science Foundation

Awards: Collaborative Research: SWIFT: SMALL: Learning-Efficient Spectrum Access for No-Sensing Devices in Shared Spectrum, Collaborative Research: MLWiNS: Dino-RL: A Domain Knowledge Enriched Reinforcement Learning Framework for Wireless Network Optimization, CNS Core: Medium: When Next Generation Wireless Networks Meet Machine Learning

OpenAlex ID: W4393305228

FWCI: 0.147

Cites: 49

Cited by: 1

Related to: 10