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ETD Abstract Container

Abstract Header

Deep Reinforcement Learning for Open Multiagent System

Zhu, Tianxing
http://orcid.org/0000-0001-9985-1216
http://rave.ohiolink.edu/etdc/view?acc_num=oberlin1657560230409707

Abstract Details

2022, BA, Oberlin College, Computer Science.
In open multiagent systems, multiple agents work together or compete to reach the goal while members of the group change over time. For example, intelligent robots that are collaborating to put out wildfires may run out of suppressants and have to leave the place to recharge; the rest of the robots may need to change their behaviors accordingly to better control the fires. Thus, openness requires agents not only to predict the behaviors of others, but also the presence of other agents. We present a deep reinforcement learning method that adapts the proximal policy optimization algorithm to learn the optimal actions of an agent in open multiagent environments. We demonstrate how openness can be incorporated into state-of-the-art reinforcement learning algorithms. Simulations of wildfire suppression problems show that our approach enables the agents to learn the legal actions.
Adam Eck (Advisor)
16 p.
Artificial Intelligence; Computer Science
Reinforcement learning; Multiagnet systems; Artificial intelligence; Open environment; Deep reinforcement learning; Neural networks; Markov decision process

Recommended Citations

Citations

  • Zhu, T. (2022). Deep Reinforcement Learning for Open Multiagent System [Undergraduate thesis, Oberlin College]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=oberlin1657560230409707

    APA Style (7th edition)

  • Zhu, Tianxing. Deep Reinforcement Learning for Open Multiagent System. 2022. Oberlin College, Undergraduate thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=oberlin1657560230409707.

    MLA Style (8th edition)

  • Zhu, Tianxing. "Deep Reinforcement Learning for Open Multiagent System." Undergraduate thesis, Oberlin College, 2022. http://rave.ohiolink.edu/etdc/view?acc_num=oberlin1657560230409707

    Chicago Manual of Style (17th edition)

oberlin1657560230409707
135
© 2022, all rights reserved.
This open access ETD is published by Oberlin College Honors Theses and OhioLINK.