Work

Deep Reinforcement Learning in Labor Market Simulations

Year: 2025

Type: conference-paper

Source: IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr)

DOI: 10.1109/cifer64978.2025.10975741

Authors: Ruxin Chen, Zeqiang Zhang

Institutions: Nagoya University, Universität Ulm

Language: English

Topic: Multi-Agent Systems and Negotiation

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Decent work and economic growth

Open Access status: closed

OpenAlex ID: W4409797038

FWCI: 0.984

Cites: 30

Cited by: 1

Related to: 10