If the heuristic function is zero, this algorithm degenerates into Dijkstra's algorithm.
A type of ant colony optimization based on this algorithm has been applied by Gan et al to provide partial and negative outcome solutions to combinatorial auction maximization dilemmas. The ALPH variant of this algorithm is more adaptive and better at breaking ties than the original. Another modification has improved accuracy and is often used in AI known as the Iterative Deepening variant. The Lifelong Planning version is useful when costs are constantly changing (*) but requires a large amount of memory, while the Beam Search limits the size of its open search but requires the set to be sorted. It employs a priority queue known as the open set, and combines both a heuristic function and a cost function to balance path-finding considerations. If the heuristic function is zero, this algorithm degenerates into Dijkstra's algorithm. First developed by Peter Hart, Nils Nilsson, and Bertram Raphael, for ten points, name this best-first graph search algorithm which seeks the least-cost path to one of several goal nodes.
A type of ant colony optimization based on this algorithm has been applied by Gan et al to provide partial and negative outcome solutions to combinatorial auction maximization dilemmas.
A* [{pronounced} “{A}-{star}”]