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Title: Learning cooperative behaviours in complex 3D games with multi-agent reinforcement learning
Authors: Lim, Yuan Jie
Keywords: Engineering::Computer science and engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Lim, Y. J. (2022). Learning cooperative behaviours in complex 3D games with multi-agent reinforcement learning. Final Year Project (FYP), Nanyang Technological University, Singapore.
Project: SCSE21-0508
Abstract: Multi-Agent systems can be used to deal with plenty of real world problems in almost any industry(Robotics, Distributed Control, Telecommunication,etc). In these industries most of these problems would be complex and often the solutions would require a group of agents that must cooperate and coordinate their action.Through Multi-Agent Reinforcement Learning(MARL) multiple agents will interact with each other in the same environment, either cooperatively or competitively using centralized training with decentralized execution. This project aims to analyse MARL algorithms, selecting the algorithm with the most potential that would be able to learn cooperative behaviours effectively and how it would be compared to other RL algorithms.
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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