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Week 2 Project of edX (Columbia) Artificial Intelligence Course. Uses BFS, DFS, A* searches to solve 8 board puzzle.

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edxProject1

Week 2 Project of edX (Columbia) Artificial Intelligence Course that got 100%. Implemented BFS, DFS, A* searches (as well as Priority Queue) to solve 8 board puzzle. http://mypuzzle.org/sliding has an example of that game.

Instruction

Your job in this assignment is to write driver.py, which solves any 8-puzzle board when given an arbitrary starting configuration. The program will be executed as follows:

$ python driver.py <method> <board>

The method argument will be one of the following. You need to implement all three of them:

1. bfs (Breadth-First Search)

2. dfs (Depth-First Search)

3. ast (A-Star Search)

The board argument will be a comma-separated list of integers containing no spaces. For example, to use the bread-first search strategy to solve the input board given by the starting configuration {0,8,7,6,5,4,3,2,1}, the program will be executed like so (with no spaces between commas):

$ python driver.py bfs 0,8,7,6,5,4,3,2,1

Output

When executed, your program will create / write to a file called output.txt, containing the following statistics:

1. path_to_goal: the sequence of moves taken to reach the goal

2. cost_of_path: the number of moves taken to reach the goal

3. nodes_expanded: the number of nodes that have been expanded

4. search_depth: the depth within the search tree when the goal node is found

5. max_search_depth:  the maximum depth of the search tree in the lifetime of the algorithm

6. running_time: the total running time of the search instance, reported in seconds

7. max_ram_usage: the maximum RAM usage in the lifetime of the process as measured by the ru_maxrss attribute in the resource module, reported in megabytes

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Week 2 Project of edX (Columbia) Artificial Intelligence Course. Uses BFS, DFS, A* searches to solve 8 board puzzle.

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