Analisis Deskriptif Penerapan Sistem Navigasi Peta Pada Video Gim ‘Grand Theft Auto: IV’


Authors

  • Hariz Kurniawan Universitas Palangka Raya, Palangka Raya, Indonesia
  • Hefi Kristianto Universitas Palangka Raya, Palangka Raya, Indonesia
  • Willy Azrieel Universitas Palangka Raya, Palangka Raya, Indonesia
  • Ressa Priskilla Universitas Palangka Raya, Palangka Raya, Indonesia
  • Viktor Handrianus Pranatawijaya Universitas Palangka Raya, Palangka Raya, Indonesia

DOI:

https://doi.org/10.47065/bulletincsr.v4i3.349

Keywords:

Grand Theft Auto IV; Video Game; Navigation System; Artificial Intelligence; Pathfinding Algorithm; Observation

Abstract

Grand Theft Auto IV is one of the groundbreaking installments in the renowned franchise that has shaken up the video game industry. Showcasing the captivating fictional city of Liberty City, the game entices users to explore and immerse themselves in its world. To enhance the immersive experience and facilitate exploration, the game introduces a revolutionary map navigation system. This revolutionary navigation system piqued our interest, leading us to uncover the secrets behind its success in addressing the common navigation issues faced by players over the past decade. This study aims to examine the functionality and application of artificial intelligence within this acclaimed navigation system. Utilizing a descriptive analysis method, we investigated the workings, types, and role of the pathfinding algorithms employed in the map navigation system. The system offers two navigation options, visual and audio, both powered by Dijkstra's algorithm. This algorithm calculates the shortest route between the player’s current position and the set destination. Additionally, the adaptive voice selection algorithm brings the calculated route to life through verbal instructions. In terms of performance, the visual navigation system excels with a route calculation time of 2.064 seconds, while the audio navigation system is slower at 6.009 seconds. Despite this, both navigation systems effectively assist users in navigating the complexities of Liberty City.

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References

H. Mela and K. Barznji, “Article Narrative Review Artificial Intelligence and Game Development Hemn mela Karim Barznji,” no. January, pp. 0–8, 2019.

J. Leung et al., “Extended hours of video game play and negative physical symptoms and pain,” Comput. Human Behav., vol. 155, no. February, 2024, doi: 10.1016/j.chb.2024.108181.

A. Nguyen and D. Bavelier, “Play in video games,” Neurosci. Biobehav. Rev., vol. 153, no. March, 2023, doi: 10.1016/j.neubiorev.2023.105386.

E. Goh, O. Al-Tabbaa, and Z. Khan, “Unravelling the complexity of the Video Game Industry: An integrative framework and future research directions,” Telemat. Informatics Reports, vol. 12, no. March, p. 100100, 2023, doi: 10.1016/j.teler.2023.100100.

W. Bart, “Can artificial intelligence identify creativity?: An empirical study,” J. Creat., vol. 33, no. 2, p. 100057, 2023, doi: 10.1016/j.yjoc.2023.100057.

J. M. Górriz et al., “Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends,” Inf. Fusion, vol. 100, no. July, p. 101945, 2023, doi: 10.1016/j.inffus.2023.101945.

Z. Hu, C. Fan, Q. Zheng, W. Wu, and B. Liu, “Asyncflow: A visual programming tool for game artificial intelligence,” Vis. Informatics, vol. 5, no. 4, pp. 20–25, 2021, doi: 10.1016/j.visinf.2021.11.001.

O. Ali and L. Kallach, “ScienceDirect ScienceDirect Artificial Intelligence Enabled Human Resources Recruitment Functionalities?: A Scoping Review Artificial Intelligence Enabled Human Resources Recruitment Functionalities?:,” Procedia Comput. Sci., vol. 232, pp. 3268–3277, 2024, doi: 10.1016/j.procs.2024.02.142.

J. E. A. Tadeo, “Deconstruction of Themes in ‘ Grand Theft Auto IV ,’” vol. 12, no. July, pp. 15–29, 2020.

M. Morawski and S. Wolff-Seidel, “Gaming & Geography (Education): A Model of Reflexive Analysis of Space & Action in Video Games,” Eur. J. Geogr., vol. 14, no. 3, pp. 1–19, 2023, doi: 10.48088/ejg.m.mor.14.3.001.019.

Bonifacius Vicky Indriyono and Widyatmoko, “Optimization of Breadth-First Search Algorithm for Path Solutions in Mazyin Games,” Int. J. Artif. Intell. Robot., vol. 3, no. 2, pp. 58–66, 2021, doi: 10.25139/ijair.v3i2.4256.

S. R. Lawande, G. Jasmine, J. Anbarasi, and L. I. Izhar, “A Systematic Review and Analysis of Intelligence-Based Pathfinding Algorithms in the Field of Video Games,” Appl. Sci., vol. 12, no. 11, Jun. 2022, doi: 10.3390/app12115499.

V. Bulitko and R. Lawrence, “Game-map Pathfinding with Per-Problem Selection of Synthesized Heuristics,” IEEE Conf. Comput. Intell. Games, CIG, pp. 1–4, 2023, doi: 10.1109/CoG57401.2023.10333175.

R. Drezewski and J. Solawa, “The application of selected modern artificial intelligence techniques in an exemplary strategy game,” Procedia Comput. Sci., vol. 192, pp. 1914–1923, 2021, doi: 10.1016/j.procs.2021.08.197.

G. Pentheny, “Efficient Crowd Simulation for Mobile Games,” Game AI Pro 360, pp. 77–84, 2019, doi: 10.1201/9780429055096-8.

D. Foead, A. Ghifari, M. B. Kusuma, N. Hanafiah, and E. Gunawan, “A Systematic Literature Review of A*Pathfinding,” Procedia Comput. Sci., vol. 179, no. 2020, pp. 507–514, 2021, doi: 10.1016/j.procs.2021.01.034.

J. Adler and B. F. Ramadhan, “Penerapan Algoritma Dijkstra Pada Game Learning Matematika Berbasis Android,” Komputika J. Sist. Komput., vol. 10, no. 2, pp. 173–181, 2021, doi: 10.34010/komputika.v10i2.4551.

Y. Y. N. Ng, C. W. Khong, and R. J. Nathan, “Evaluating Affective User-Centered Design of Video Games Using Qualitative Methods,” Int. J. Comput. Games Technol., vol. 2018, 2018, doi: 10.1155/2018/3757083.

C. I. Teng, T. L. Huang, G. L. Huang, C. N. Wu, T. C. E. Cheng, and G. Y. Liao, “Creatability, achievability, and immersibility: New game design elements that increase online game usage,” Int. J. Inf. Manage., vol. 75, no. October 2023, p. 102732, 2024, doi: 10.1016/j.ijinfomgt.2023.102732.

T. Jordan and M. Dhamala, “Video game players have improved decision-making abilities and enhanced brain activities,” Neuroimage: Reports, vol. 2, no. 3, p. 100112, 2022, doi: 10.1016/j.ynirp.2022.100112.

H. Manner, “Exploring the constraints on artificial general intelligence: a game-theoretic model of human vs machine interaction,” Econ. Lett., p. 109231, 2020, doi: 10.1016/j.mathsocsci.2024.03.004.

M. Ur Rehman, A. Shafique, Q. U. A. Azhar, S. S. Jamal, Y. Gheraibia, and A. B. Usman, “Voice disorder detection using machine learning algorithms: An application in speech and language pathology,” Eng. Appl. Artif. Intell., vol. 133, no. PA, p. 108047, 2024, doi: 10.1016/j.engappai.2024.108047.


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Submitted: 2024-04-06
Published: 2024-04-30

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How to Cite

Hariz Kurniawan, Hefi Kristianto, Willy Azrieel, Ressa Priskilla, & Viktor Handrianus Pranatawijaya. (2024). Analisis Deskriptif Penerapan Sistem Navigasi Peta Pada Video Gim ‘Grand Theft Auto: IV’. Bulletin of Computer Science Research, 4(3), 282-289. https://doi.org/10.47065/bulletincsr.v4i3.349

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