A Comparative Study of Informed and Uninformed Search Algorithm to Solve Eight-Puzzle Problem

Problems in artificial intelligence can be solved using intelligent tracking methods through search mechanisms. Understandably, algorithm performances are highly dependent on the problem solved. In this study, we evaluate and compare performance of five uninformed informed (breadth-first search, depth first optimal best two heuristic functions, namely mismatched tile Manhattan distance) algorithms to solve eight-puzzle game problem. For each algorithm, numbers raised explored nodes were assessed analyzed. Our experiment demonstrates that with outperforms significantly, both terms memory usage efficiency computational power efficiency. On average, requires only 5.33% used by 4.45% demanded search. Boxplot analysis also confirms delivers more stable contrasted These could a concern for researchers developers consider implementing heuristically enhanced utilize efficiently similar problems.