Editing A* search algorithm (section)

===Special cases===
[[Dijkstra's algorithm]], as another example of a uniform-cost search algorithm, can be viewed as a special case of A* where {{tmath|1=h(x) = 0}} for all ''x''.<ref name="geospatial">{{citation|title=Geospatial Analysis: A Comprehensive Guide to Principles, Techniques and Software Tools|first1=Michael John|last1=De Smith|first2=Michael F.|last2=Goodchild|first3=Paul|last3=Longley|publisher=Troubadour Publishing Ltd|year=2007|isbn=9781905886609|page=344|url=https://books.google.com/books?id=SULMdT8qPwEC&pg=PA344}}.</ref><ref name="pythalgs">{{citation |last=Hetland |first=Magnus Lie |title=Python Algorithms: Mastering Basic Algorithms in the Python Language |page=214 |year=2010 |url=https://books.google.com/books?id=9_AXCmGDiz8C&pg=PA214 |archive-url=https://web.archive.org/web/20220215222823/https://books.google.com/books?id=9_AXCmGDiz8C&pg=PA214 |archive-date=15 February 2022 |publisher=Apress |isbn=9781430232377}}.</ref> General [[depth-first search]] can be implemented using A* by considering that there is a global counter ''C'' initialized with a very large value. Every time we process a node we assign ''C'' to all of its newly discovered neighbors. After every single assignment, we decrease the counter ''C'' by one. Thus the earlier a node is discovered, the higher its {{tmath|h(x)}} value. Both Dijkstra's algorithm and depth-first search can be implemented more efficiently without including an {{tmath|h(x)}} value at each node.