Learning cooperative behaviours in complex 3D games with multi-agent reinforcement learning

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 coor...

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Main Author:	Lim, Yuan Jie
Other Authors:	Lana Obraztsova
Format:	Final Year Project
Language:	English
Published:	Nanyang Technological University 2022
Subjects:	Engineering::Computer science and engineering
Online Access:	https://hdl.handle.net/10356/156606
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-156606
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spelling	sg-ntu-dr.10356-1566062022-04-21T02:43:17Z Learning cooperative behaviours in complex 3D games with multi-agent reinforcement learning Lim, Yuan Jie Lana Obraztsova School of Computer Science and Engineering lana@ntu.edu.sg Engineering::Computer science and engineering 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. Bachelor of Engineering (Computer Science) 2022-04-21T02:43:17Z 2022-04-21T02:43:17Z 2022 Final Year Project (FYP) Lim, Y. J. (2022). Learning cooperative behaviours in complex 3D games with multi-agent reinforcement learning. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156606 https://hdl.handle.net/10356/156606 en SCSE21-0508 application/pdf Nanyang Technological University
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	Engineering::Computer science and engineering
spellingShingle	Engineering::Computer science and engineering Lim, Yuan Jie Learning cooperative behaviours in complex 3D games with multi-agent reinforcement learning
description	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.
author2	Lana Obraztsova
author_facet	Lana Obraztsova Lim, Yuan Jie
format	Final Year Project
author	Lim, Yuan Jie
author_sort	Lim, Yuan Jie
title	Learning cooperative behaviours in complex 3D games with multi-agent reinforcement learning
title_short	Learning cooperative behaviours in complex 3D games with multi-agent reinforcement learning
title_full	Learning cooperative behaviours in complex 3D games with multi-agent reinforcement learning
title_fullStr	Learning cooperative behaviours in complex 3D games with multi-agent reinforcement learning
title_full_unstemmed	Learning cooperative behaviours in complex 3D games with multi-agent reinforcement learning
title_sort	learning cooperative behaviours in complex 3d games with multi-agent reinforcement learning
publisher	Nanyang Technological University
publishDate	2022
url	https://hdl.handle.net/10356/156606
_version_	1731235771162034176

Learning cooperative behaviours in complex 3D games with multi-agent reinforcement learning

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