Help:

In this homework you will use Python to implement basic graph search we have covered in class, namely the Depth$-$First Search $($DFS$),$ Breadth$-$First Search $($BFS$),$ and Uniform Cost Search $($UCS$).$ Implementing these algorithms in program code is important, as they are the basis for advanced search and planning methods and building blocks of the major part of this course.

The homework should be done in Python $($Python $3.$X is recommended$).$ Include a documentation $($in $.$doc or $.$pdf format$)$ that describes the complete steps of your solutions for each problem including: $(1)$ The answer to any questions posed, $(2)$ any results $($include print outs or terminal outputs$),$ and $(3)$ the name of any Python module$($s$)$ and function$($s$)($Numpy$,$ Matplotlib, etc.$)$ you used. Discussion is allowed, but you must submit your own write$-$up and list your collaborators.

Zip all your documents with the source code $(.$py files, if there are self$-$implemented modules, organize them in different folders$),$ documentation, and data $($image files, text, etc.$)$ into a file called $[$Lastname$\_$FirstInitial$\_$Homework$1.$zip$]$ and upload it to the Brightspace prior to the due date.

Make sure your code works when you send it out. Please use as less third$-$party libraries as possible cause it is easy for instructors to reproduce your results. If you used the libraries that requires installation, please list the dependencies and its version in your README file or using pip to generate the dependency list like pip freeze $>$ requirements.txt$.$

$($see picture for the rest of doc$)$