README.md 3.4 KB
Visualisation of A* Search using networkx library
A* Search
A* search( pronounced as "A star") is a search algorithm which explores a graph by expanding the that node which minimizes steps from the source(like in BFS) as well as approximate steps to the goal(like in greedy bfs). Hence, this algorithm is thorough and fast as it combines the strengths of both BFS and Greedy BFS. A* algorithm is proven to give the optimal solution to a problem.
What is the evaluation function here?
Evaluation function-f is the criterion based on which the next node is chosen. f is the sum of 2 parameters:
- cost of path from source to the given node
- approximate cost of reaching the goal from the given node (heuristic function) So, at each step, the node is chosen such that sum of the above 2 parameters, that is, f is minimal.
Algorithm
Starting from source city, we choose the next city such that it is in the shortest path from the source (based on the cost of the route from source) as well as the closest to the Goal city(based on the heuristics function) amongst all it's neighbours. We terminate, once we've reached the goal city.
Let us understand this better through an example.
Source: Artificial Intelligence A Modern Approach
by Stuart J. Russell and Peter Norvig
Given here is the map of Romania with cities and distance between them. We need to find the shortest route from Arad to Bucharest.
The heurestics that we are using here is the straight-line distance from the city to the goal(Here, Bucharest). Note that, this straight line distance is obtained only by knowing the map coordinates of the 2 cities.
Input
Input is taken from the file
input.txt
Each line in the input is of the form
city1 city2 dist
It denotes each element of the adjacency list. That is, dist is the distance between city1 and city2. An undireced graph is drawn depicting the map of Romania. Starting city: Arad Goal city: Bucharest
Heuristics is loaded from the file
heuristics.txt
Each line is of the form
city h
'h' stands for the heuristics value(here, the straight line distnace) from the city 'city' to goal city(here, Bucharest)
Working:
Here, Arad is the starting city. The first node to be expanded from Arad will be Sibiu, because it has a smaller value of f (140+253=393) than either Zerind (75+374=449_)or Timisoara(118 + 329 =447). The next node to be expanded will be Rimnicu_Vilcia, because it has a smaller f compared to other possible nodes. Similary, Pitesti is expanded next and finally Bucharest is reached.
Here, is the resultant graph.
Green coloured node denotes the starting city(Here, Arad).
Red coloured node denotes the goal city(Here, Bucharest).
Edges marked with black is the route from Arad to Bucharest generated by the A* search algorithm.
Complexity
Time: O(b^d)
b - Branching factor, the average number of successors per state
d - depth of the shortest path