Description
Problem 1:
Consider the following graph (credit Knuth 2008, p. 15):
Write six Python scripts implementing depth-first search (DFS), breadth-first search (BFS), and Iterative
Deepening Search (IDS), each with and without a visited list. Use these algorithms to solve for a simple
path from S G, where S is Washington (WA) and G is Georgia (GA). Ties will be broken in alphabetical
order. Augment your implementation to report the computational time, # of paths popped from the
queue, maximum queue size, and length of returned path. You may manually define the graph in python
or grab a definition from online. Submit a PDF of this page having filled in these rows and columns:
Visited
List
Time (s) # Paths Popped
from Queue
Max Queue
Size
Returned Path’s
Length/Cost
DFS No
Yes
BFS No
Yes
IDS No
Yes
You should have one Python file for each type of search, and the code should be clearly documented. Files
should be named “[METHOD]_[VISITED].py” (e.g., “dfs_yes.py”). Further, when the grader runs the
python code, the script should print to the screen the relevant information reported in the table above.
Remember, if it does not run, you do not receive credit.