Enhancing action maze video games using Shuffled Frog Leaping Algorithm

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.