@@ -0,0 +1,1381 @@
+def dist_between(current,neighbor):%0A    return 0%0A%0Adef heuristic_cost_estimate(start,goal):%0A    return 0%0A%0Adef reconstruct_path(cameFrom, currentNode):%0A    return 0%0A%0Adef neighbor_nodes(current):%0A    return %7B1: 2, 3: 4%7D%0A%0Adef aStar(start,goal):%0A    closedSet = %7B%7D%0A    openSet = %7Bstart%7D%0A    cameFrom = %7B%7D%0A    gScore = %7B%7D%0A    gScore%5Bstart%5D = 0%0A    fScore = %7B%7D%0A    fScore%5Bstart%5D = gScore%5Bstart%5D+heuristic_cost_estimate(start,goal)%0A    while len(openSet) != 0:%0A        #current = 0 the node in openSet having the lowest fScore%5B%5D value%0A        current = 0%0A        if current == goal:%0A            return reconstruct_path(cameFrom,goal)%0A        #remove current from openSet%0A        #add current to closedSet%0A        for neighbor in neighbor_nodes(current):%0A            tentative_gScore = gScore%5Bcurrent%5D + dist_between(current,neighbor)%0A            if neighbor in closedSet and tentative_gScore %3E= gScore%5Bneighbor%5D:%0A                continue%0A            if neighbor not in closedSet or tentative_gScore %3C gScore%5Bneighbor%5D:%0A                cameFrom%5Bneighbor%5D = current%0A                gScore%5Bneighbor%5D = tentative_gScore%0A                fScore%5Bneighbor%5D = gScore%5Bneighbor%5D + heuristic_cost_estimate(neighbor,goal)%0A                if neighbor not in openSet:%0A                    test = 0%0A                    #add neighbor to openSet%0A    return 1%0A%0Aif __name__ == %22__main__%22:%0A    print aStar(0,1)%0A

Create aStar.py