Assignment Description:

In this assignment, you will work with a specific search space to better understand different search strategies used in artificial intelligence. You will visualize and compare the results of four search algorithms $-$ Breadth$-$First Search, Depth$-$First Search, and Iterative Deepening Search $-$ as they navigate through a given state space to find a path from the initial state to the goal state.

Task: You are given the following search space:

State Next Cost

A B $4$

A C $1$

B D $3$

B E $8$

C C $0$

C D $2$

C F $6$

D C $2$

D E $4$

E G $2$

F G $8$

Part A: State Space Visualization

Create a visual representation of the given state space. Use nodes to represent states $($e$.$g$.,$ A$,$ B$,$ C$)$ and edges to indicate possible transitions between states, along with their associated costs and heuristic values.

Part B: Search Strategy Comparison

Assume that the initial state is A$,$ and the goal state is G$.$ Explore how each search strategy creates a search tree to find a path from the initial state to the goal state. Moreover, shows which node is being expanded and the fringe content for each algorithm step.

I. Breadth$-$First Search $($BFS$)$

II$.$ Depth$-$First Search $($DFS$)$

III. Iterative Deepening Search $($IDS$)$

Instructions:

$1.$ Draw the state space $($Part A$)$ and document the search tree progress for each search strategy $($Part B$).$

$2.$ Use a clear search tree and brief descriptions to illustrate each step of the algorithms.

$3.$ Compare and analyze the differences in search strategies and their efficiency in finding the optimal path from the initial state A to the goal state G$.$