BALANCING OF PERSONAL AND GROUP GOALS FOR AGENTS USING MULTI-AGENT REINFORCEMENT LEARNING
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Date
2022-04
Authors
Zhabinets, Maxim
Journal Title
Journal ISSN
Volume Title
Publisher
Nazarbayev University School of Engineering and Digital Sciences
Abstract
The number of AI agents in the world is increasing every day and they will need to
interact with each other. It is in humanity’s best interest to teach these agents to
respect the goals of others and live in harmony. In this study, we try to balance the
personal and group goals of agents in social dilemma scenarios using the Proximal
Policy Optimisation algorithm for both a decentralized learning approach and a centralized
learning approach. After this, we compare the results of both approaches
and point out their strong and weak points. We also test the impact of using an
inequity-averse penalty that penalizes policies resulting in unequal rewards for agents
in both decentralized and centralized learning. We briefly describe the history of
multi-agent learning. We then look at the latest achievements in the application of
centralized and decentralized multi-agent learning approaches, focusing on methods
of balancing agents’ personal preferences with group goals. Next, the thesis describes
the environments and methods used in this study. Then we describe the details of
the performed experiments and discuss the results. We show that both centralized
and decentralized learning approaches have their advantages and discuss them. We
also show that inequity averse penalty is an efficient technique for balancing of the
agents reward in social dilemma environments.
Description
Keywords
Research Subject Categories::TECHNOLOGY, Type of access: Open Access, Proximal Policy Optimisation algorithm, AI, artificial intelligence, Multi-Agent Reinforcement Learning, decentralized learning, Reinforcement Learning
Citation
Zhabinets, M. (2022). BALANCING OF PERSONAL AND GROUP GOALS FOR AGENTS USING MULTI-AGENT REINFORCEMENT LEARNING (Unpublished master's thesis). Nazarbayev University, Nur-Sultan, Kazakhstan