Enhancing action maze video games using shuffled frog leaping algorithm

Name: Gharde, Dheeraj

Organization : PES University. Computer Science dept.

Email : gharde.dheeraj@gmail.com

Name: N., Suryanarayan

Organization : PES University. Computer Science dept.

Email : surya.narayan0707@gmail.com

Name: Prasad, V. R. Badri

Organization : PES University. Computer Science dept.

Email : badriprasad@pes.edu

LCSH: Video games in education

LCSH: Computer algorithms

LCSH: Computational intelligence

Abstract: Shuffled Frog Leaping Algorithm(SFLA) is a very popular population-based meta-heuristic algorithm, created by Eusuff and Lansey in 2006. Because of its limited variables and easiness in implementation, it is used in memetics and particle swarm optimization to give several use cases. We believe one unexplored application of this algorithm is in video games, primarily in the genre of action based video games. They involve optimizations in path planning and navigation where SFLA can be utilized. We also believe these games can serve as simulations for real-life scenarios of navigation, thereby giving a virtual environment to enhance this algorithm further. Finally, we compare this method with popular nature based ones such as BFA and SPPSO algorithms and conclude on their optimization efficiency for action maze video games like Pac-Man

King Mongkut's University of Technology North Bangkok. Central Library

Address: BANGKOK

Email: library@kmutnb.ac.th

Created: 2022

Modified: 2024-05-23

Issued: 2024-05-23

BibliograpyCitation : In IEEE Computer Society. 2022 Fifth International Conference on Computational Intelligence and Communication Technologies (CCICT 2022) (pp.432-438). Los Alamitos, CA : IEEE Computer Society

eng

©copyrights

ลำดับที่.	ชื่อแฟ้มข้อมูล	ขนาดแฟ้มข้อมูล	จำนวนเข้าถึง	วัน-เวลาเข้าถึงล่าสุด
1	CCICT 2022pp.432-438.pdf	390.31 KB

ใช้เวลา

0.031508 วินาที