A comparison of Intelligent Water Drops and Genetic Algorithm for maze solving

Abstract: Evolutionary and swarm based algorithms are subsets of bio-inspired algorithms where    Genetic Algorithm (GA) belongs to the former and Intelligent Water Drops (IWD) to the latter.      In this report we investigate their ability to solve mazes with different complexity.    As performance measures we compare solution quality and success rates.    We find that IWD outperforms GA on mazes of low complexity but results deteriorate quickly as maze complexity increases. GA produces more stable results, better solution quality and a higher success rate for high complexity mazes. Some potential improvements inspired by other works are discussed. We conclude that examining different improvements through stronger subordinate problem-specific heuristics is of interest.