modify search.py and searchagent.py in pyhton for dfs$,$bfs$,$ uniform search, nullheurstic, a$*$ and cornersproblem

In this lab, your Pacman agent will find paths through his maze world, both to reach a

particular location and to collect food efficiently. You will build general search

algorithms and apply them to Pacman scenarios.

This lab includes an autograder for you to grade your answers on your machine. This

can be run with the command:

python autograder.py

The code for this lab consists of several Python files, some of which you will need to

read and understand in order to complete the assignment, and some of which you can

ignore. You can download all the code and supporting files as a zip archive $($search$.$zip$).$

Files you'll edit:

search.py Where all of your search algorithms will reside.

searchAgents.py Where all of your search$-$based agents will reside.

Files you might want to look at:

pacman.py

The main file that runs Pacman games. This file describes a Pacman

GameState type, which you use in this lab.

game.py

The logic behind how the Pacman world works. This file describes

several supporting types like AgentState, Agent, Direction, and Grid.

util.py Useful data structures for implementing search algorithms.

Supporting files you can ignore:

graphicsDisplay.py Graphics for Pacman

graphicsUtils.py Support for Pacman graphics

textDisplay.py ASCII graphics for Pacman

ghostAgents.py Agents to control ghosts

keyboardAgents.py Keyboard interfaces to control Pacman

layout.py Code for reading layout files and storing their contents

autograder.py Lab autograder

testParser.py Parses autograder test and solution files

testClasses.py General autograding test classes

test$\_$cases$/$ Directory containing the test cases for each question

searchTestClasses.py Lab $1$ specific autograding test classes

Files to Edit and Submit: You will fill in portions

of search.py and searchAgents.py during the assignment. You should submit these files

with your code and comments. Please do not change the other files in this distribution

or submit any of the original files other than these files.

Evaluation: Your code will be autograded for technical correctness. Please do not

change the names of any provided functions or classes within the code, or you will

wreak havoc on the autograder. However, the correctness of your implementation $$ not

the autograder$$s judgements $$ will be the final judge of your score.

Academic Dishonesty: We will be checking your code against other submissions in the

class for logical redundancy. If you copy someone else$$s code and submit it with minor

changes, we will know. These cheat detectors are quite hard to fool, so please don$$t try.

We trust you all to submit your own work only; please don$$t let us down. If you do$,$ we

will pursue the strongest consequences available to us$.$

Discussion: You can use the Discussion page set up for this lab to inquire and get

clarifications, but please be careful not to post spoilers.

Welcome to Pacman

After downloading the code, unzipping it$,$ and changing to the directory, you should be

able to play a game of Pacman by typing the following at the command line:

python pacman.py

Pacman lives in a shiny blue world of twisting corridors and tasty round treats.

Navigating this world efficiently will be Pacman$$s first step in mastering his domain.

The simplest agent in searchAgents.py is called the GoWestAgent, which always goes

West $($a trivial reflex agent$).$ This agent can occasionally win:

python pacman.py $--$layout testMaze $--$pacman GoWestAgent

But, things get ugly for this agent when turning is required:

python pacman.py $--$layout tinyMaze $--$pacman GoWestAgent

If Pacman gets stuck, you can exit the game by typing CTRL$-$c into your terminal.

Soon, your agent will solve not only tinyMaze, but any maze you want.

Note that pacman.py supports a number of options that can each be expressed in a long

way $($e$.$g$.,--$layout$)$ or a short way $($e$.$g$.,-$l$).$ You can see the list of all options and their

default values via:

python pacman.py $-$h

Also, all of the commands that appear in this lab also appear in commands.txt$,$ for easy

copying and pasting. In UNIX$/$Mac OS X$,$ you can even run all these commands in order

with bash commands.txt$.$

Q$1(12$ pts$)$: Finding a Fixed Food Dot using Depth First

Search

In searchAgents.py$,$ you$$ll find a fully implemented SearchAgent, which plans out a path

through Pacman$$s world and then executes that path step$-$by$-$step. The search

algorithms for formulating a plan are not implemented $$ that$$s your job.

First, test that the SearchAgent is working correctly by running:

python pacman.py $-$l tinyMaze $-$p SearchAgent $-$a fn$=$tinyMazeSearch

The command above tells the SearchAgent to use tinyMazeSearch as its search algorithm,

which is implemented in search.py$.$ Pacman should navigate the maze successfully.

Now it$$s time to