Adaptive game antagonists generation and evolution approach for a COVID-19 pandemic concept role-playing game / by Alexander Cane C. Chan, Angelica Marie E. Co, Joylyn M. Lopez and Vanessa Jane A. Mojica.

By:

Chan, Alexander Cane C [author]

Contributor(s):

Material type: Text

TextLanguage: English Publication details: Indang, Cavite : Cavite State University- Main Campus, 2022.Description: xvi, 98 pages : illustrations ; 28 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

Subject(s):

DDC classification:

005.1 C36 2022

Online resources:

Click here to view the Abstract and Table of Contents

Production credits:

College of Engineering, and Information Technology (CEIT)

Abstract: CHAN, ALEXANDER CANE C., CO, ANGELICA MARIE E., LOPEZ, JOYLYN M., and MOJICA, VANESSA JANE A. Adaptive Game Antagonists Generation and Evolution Approach for a Covid-19 Pandemic Concept Role-Playing Game. Undergraduate thesis. Bachelor of Science in Computer Science. Cavite State University, Indang, Cavite. June 2022. Adviser: Ms. Ezra Marie E. Ramos. This research was carried out at Cavite State University - Main Campus from September 2021 to June 2022. The goal of this study is to develop Pandemic Quest Survival, a 3D mobile game that shows how genetic algorithms may be used in games in a way that can educate users about different CoVid-19 variants as well as how to employ it in enemy spawning. Pandemic Quest Survival uses GA to provide the required incremental change in game complexity as well as a dynamic adjustment in game level difficulty. The game application was hard coded in Visual Studio using tools such as UNITY Game Engine, Unity Hub, and C#. To test some of the game's functionality, the researchers used Test Driven Development, which creates small test cases for each feature's functionality based on the initial understanding of the game; if the test fails to run properly, the code must be changed; and if the test runs successfully, it ensures that the game process has been improved and meets the required requirements. The proposed research received a "Very Good" grade from both technical and non-technical participants as a result of the ISO/IEC 9126 application. Functionality, reliability, usability, efficiency, maintainability, portability, and user- friendliness were all indicators assessed in order to determine the game compliance to standard and studies objectives. Non-technical participants awarded the Pandemic Quest Survival Quest a 4.32 rating, while technical participants gave it a 4.44. This research found that this game satisfies the aims of the study and allows for adjustments throughout production, allowing it to achieve its purpose while also fitting into the broader concepts and ideas, making it more realistic. However, various game features, such as adding new levels, additional character upgrade options, and making the game available in a multiplayer setting to allow other players to play with them in order to keep the players involved in the game, are some of the suggestions made in order to improve the game.

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Holdings
Item type	Current library	Collection	Call number	Materials specified	URL	Status	Notes	Date due	Barcode
Theses / Manuscripts	Ladislao N. Diwa Memorial Library Theses Section	Non-fiction	005.1 C36 2022 (Browse shelf(Opens below))		Link to resource	Room use only	T-9119		00081996

Thesis (Bachelor of Science in Computer Science) Cavite State University

Includes bibliographical references.

College of Engineering, and Information Technology (CEIT)

CHAN, ALEXANDER CANE C., CO, ANGELICA MARIE E., LOPEZ, JOYLYN M., and MOJICA, VANESSA JANE A. Adaptive Game Antagonists Generation and Evolution Approach for a Covid-19 Pandemic Concept Role-Playing Game. Undergraduate thesis. Bachelor of Science in Computer Science. Cavite State University, Indang, Cavite. June 2022. Adviser: Ms. Ezra Marie E. Ramos.

This research was carried out at Cavite State University - Main Campus from September 2021 to June 2022. The goal of this study is to develop Pandemic Quest Survival, a 3D mobile game that shows how genetic algorithms may be used in games in a way that can educate users about different CoVid-19 variants as well as how to employ it in enemy spawning. Pandemic Quest Survival uses GA to provide the required incremental change in game complexity as well as a dynamic adjustment in game level difficulty. The game application was hard coded in Visual Studio using tools such as UNITY Game Engine, Unity Hub, and C#. To test some of the game's functionality, the researchers used Test Driven Development, which creates small test cases for each feature's functionality based on the initial understanding of the game; if the test fails to run properly, the code must be changed; and if the test runs successfully, it ensures that the game process has been improved and meets the required requirements. The proposed research received a "Very Good" grade from both technical and non-technical participants as a result of the ISO/IEC 9126 application. Functionality, reliability, usability, efficiency, maintainability, portability, and user- friendliness were all indicators assessed in order to determine the game compliance to standard and studies objectives. Non-technical participants awarded the Pandemic Quest Survival Quest a 4.32 rating, while technical participants gave it a 4.44. This research found that this game satisfies the aims of the study and allows for adjustments throughout production, allowing it to achieve its purpose while also fitting into the broader concepts and ideas, making it more realistic. However, various game features, such as adding new levels, additional character upgrade options, and making the game available in a multiplayer setting to allow other players to play with them in order to keep the players involved in the game, are some of the suggestions made in order to improve the game.

Submitted to the University Library 08/08/2022 T-9119

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