Smitha, a working professional, needs to run several errands after leaving her office. Her tasks

include:

$1.$ Visiting the supermarket to buy groceries

$2.$ Withdrawing cash from an ATM

$3.$ Dropping off clothes at the tailor shop

$4.$ Picking up medication from the medical store

$5.$ Purchasing books from the bookstore

$6.$ Picking up her daughter from the day$-$care center

After completing all these tasks, Smitha needs to return home.

The objective is to determine the most efficient route that minimizes the total distance travelled

while ensuring that Smitha visits all the required locations exactly once before reaching her home.

Given:

$$ The locations of Smitha's office, home, supermarket, ATM, tailor shop, medical store,

bookstore, and day$-$care center in the city.

$$ The distances between each pair of locations.

Your task is to implement an algorithm that finds the optimal path for Smitha to complete her

errands in the shortest possible distance. The algorithm should take into account the constraints

that each location must be visited exactly once, and the final destination is Smitha's home.

Use the following algorithms to solve the stated problem:

$1.$ Recursive Best First Search

$2.$ Depth first search

$1.$ Explain the PEAS and Task environment of the agent $[20\%$ weightage$]$

$2.$ Define the heuristic and or fitness function for the given algorithms and the given

problem. $[20\%$ weightage$]$

$3.$ Use appropriate data structures and implement given informed and uninformed

search algorithm and Print the path taken by the agent. $[40\%$ weightage$]$

$4.$ Find and print space and time complexity using code in your implementation. $[20\%$

weightage$]$

$***$ Need python code

#Code Block : Set Initial State $($Must handle dynamic inputs$)$

#Code Block : Set the matrix for transition & cost $($as relevant for the given problem$)$

#Code Block : Write function to design the Transition Model$/$Successor function. Ideally this would be called while search algorithms are implemented

#Code block : Write fucntion to handle goal test $($Must handle dynamic inputs$).$ Ideally this would be called while search algorithms are implemented

#Code Block : Function for algorithm $1$ implementation

#Code Block : Function for algorithm $2$ implementation

#Code Block : Function & call to get inputs $($start$/$end state$)$

#Invoke algorithm $1($Should Print the solution, path, cost etc., $($As mentioned in the problem$))$

#Invoke algorithm $2($Should Print the solution, path, cost etc., $($As mentioned in the problem$))$

#Code Block : Print the Time & Space complexity of algorithm $1$

#Code Block : Print the Time & Space complexity of algorithm $2$

#Provide your comparitive analysis or findings in no more than $3$ lines in below section