Little Hoody : A 2D Action-RPG Game Development By Using Finite State Machine

Lim, Beng Tiong (2020) Little Hoody : A 2D Action-RPG Game Development By Using Finite State Machine. [Final Year Project Report] (Unpublished)

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Abstract

Artificial intelligence (AI) has been widely used in various field nowadays. The AI techniques that used in video games have been improved over the years. However, the repetitive behaviours of the enemy AI is the main weakness that exists in current video games. Hence, the aim of this project is to develop a game prototype by using Finite State Machine (FSM) method to design the game AI logic for solving the existing issue and also making the enemy AI become more interactive which able to change its behaviour in unpredictable way. The literature review has clearly explained the terms for video game, game artificial intelligence and game genre. It also discussed on three different methods that can be used to develop the game AI, which are Finite State Machine, Behavioural Decision Tree and Genetic Neural Network. The methods are compared based on the specific criteria. Furthermore, the suitability of the game AI implementation methods is discussed according to the different game genres. The Finite State Machine is chosen as the main method to be used for this project. In addition, the interactive Waterfall model is selected as the methodology to develop the proposed game application. Each phase of the model is explained in detailed. The user requirement for game AI is collected from UNIMAS students through online survey. The game architecture is designed and developed based on the fundamental requirements and user requirements. Lastly, the framework is designed to visualise the user interfaces of the game system

Item Type: Final Year Project Report
Additional Information: Project Report (BSc.) -- Universiti Malaysia Sarawak, 2020.
Uncontrolled Keywords: Artificial intelligence (AI), video games, Finite State Machine (FSM), Finite State Machine, Behavioural Decision Tree and Genetic Neural Network.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Faculties, Institutes, Centres > Faculty of Computer Science and Information Technology
Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Gani
Date Deposited: 02 Feb 2021 07:54
Last Modified: 10 Jan 2024 02:08
URI: http://ir.unimas.my/id/eprint/34204

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