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Decision-making AI in digital games
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Informatics and Media, Information Systems.
2022 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The field of artificial intelligence has gained much knowledge through the implementation of decision-making systems in video games. One of these systems was the Goal Oriented Action Planning system (GOAP) which directs the behavior of an AI-agent through multiple digital artifacts categorized as goals, actions, and plans. The aim of the thesis is to aid in the understanding and creation of GOAP driven AI-agents in a video game setting to promote research on this topic. The research question of this thesis was about finding out how the GOAP architecture compares to other video game decision-making systems. The theoretical framework introduces the concept of the illusion of intelligence in video games and presents a discussion focused on the different components which make up a GOAP system and other components that support it. Additionally, the theoretical framework explains the need for a comparison between different decision-making systems and explains the social impact of game AI research. The methods section introduces the criteria for the comparison between GOAP and other decision-making systems and presents a comparison process that was driven by a literature review. A GOAP system was designed for this thesis using the unified modeling language and concept maps. It was then implemented using C# code in a free-of-charge game engine called Unity. We present the pseudocode for the implementation of the GOAP system and show that this framework is a modular, customizable, and reusable system that enables AI-agents to create plans from a varied set of actions. Finally, the paper suggests further research within game decision-making AI and emphasizes the importance of game AI research for communities of game developers, hobbyists, and others who could benefit from game AI in their projects. 

Place, publisher, year, edition, pages
2022. , p. 80
Keywords [en]
Decision-making, Goal Oriented Action Planning, GOAP, Agent, AI, Artificial Intelligence, Behavior Trees, Finite State Machines, FSM
National Category
Information Systems
Identifiers
URN: urn:nbn:se:uu:diva-477897OAI: oai:DiVA.org:uu-477897DiVA, id: diva2:1673140
Subject / course
Information Systems
Educational program
Master programme in Information Systems
Presentation
2022-05-24, Seminar Room 3, Biskopsgatan 3, 753 10 Uppsala, Uppsala, 13:15 (English)
Supervisors
Examiners
Available from: 2022-06-21 Created: 2022-06-20 Last updated: 2022-06-21Bibliographically approved

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Citation style
  • apa
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