Decision Making in Monopoly Using a Hybrid Deep Reinforcement Learning Approach-Reference-Cited by-同舟云学术

Decision Making in Monopoly Using a Hybrid Deep Reinforcement Learning Approach

Published:2022-12 Issue:6 Volume:6 Page:1335-1344
ISSN:2471-285X
Container-title:IEEE Transactions on Emerging Topics in Computational Intelligence
language:
Short-container-title:IEEE Trans. Emerg. Top. Comput. Intell.

Author:

Bonjour Trevor¹^ORCID,Haliem Marina¹^ORCID,Alsalem Aala¹^ORCID,Thomas Shilpa²,Li Hongyu²,Aggarwal Vaneet¹^ORCID,Kejriwal Mayank²^ORCID,Bhargava Bharat¹^ORCID

Affiliation:

1. Purdue University, West Lafayette, IN, USA

2. University of Southern California, Los Angeles, CA, USA

Funder

Defense Advanced Research Projects Agency

Air Force Research Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computational Mathematics,Control and Optimization,Computer Science Applications

Link

http://xplorestaging.ieee.org/ielx7/7433297/9965775/09775710.pdf?arnumber=9775710

Reference35 articles.

1. Exploiting action categories in learning complex games

2. Monopoly as a Markov Process

3. Rainbow: Combining Improvements in Deep Reinforcement Learning

4. Dueling network architectures for deep reinforcement learning;wang;Proc Int Conf Mach Learn,0

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