CS607 - Artificial Intelligence Assignment 2 Spring 2013

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Assignment No. 02
Semester: Spring 2013
CS607: Artificial Intelligence
Total Marks: 20

Due Date: 08/05/2013
Instructions
Please read the following instructions carefully before submitting assignment:
It should be clear that your assignment will not get any credit if:

§ The assignment is submitted after due date.
§ The submitted assignment does not open or file is corrupt.
§ Solution is copied from any other source.

Objective
The objective of this assignment is to enhance your knowledge about;

§ Conversion of Maps/Graphs into Trees.
§ Application of different Search Algorithms.

Assignment
Dear Student, Let’s consider we have a connectivity map/graph of Nine cities as given below. Cities are named as A, B, C…I for simplicity. The labeled edges indicate the distance in Km between connected cities e.g. the edge between node B and C is labeled as 3 which indicate that there is 3Km distance between city B and C.

Suppose you are currently at city A and you need to carry certain object to city I. In other words, your starting position is city A and destination is city I. Your task is to transform this map/graph into Tree and apply selected search techniques to find the path from A to I.

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Questions

Part 1: Draw below your Connectivity Tree of the given Map/Graph. See Page#23 in your handouts for sample conversion of graph into tree.

















Part 2: Apply the following search techniques on your connectivity tree and write the path found by each technique along with its cost in terms of total distance from A to I.

Search Technique Resultant Path/s Total Path Length/s
Sample Search A-B-C-F-H-I 2+3+3+2+3=13Km
Depth First Search
Breadth First Search
Best First Search
Beam Search (k=2)

(Sample search is just given as an example to show how you need to fill this table with desired values.)

Note:
· Total path length is the sum of all edges included in the selected path.
· Your connectivity tree shall be complete i.e. representing all possible paths from city A without any cycles/loops.
· Left Sub-tree will be processed first in Depth First Search.
· Resultant paths mainly depend upon your Tree. If your path is not correct as per your Tree then marks will be deducted.
· There is no aerial distance information available, so you have to use and make decision upon available local intercity distance information in case of Best First and Beam Search.

Submission

You are required to submit your solution in MS Word format through LMS.

Search Algorithms and Applications

Search algorithms aim to find solutions or objects with specified properties and constraints in a large solution search space or among a collection of objects. A solution can be a set of value assignments to variables that will satisfy the constraints or a sub-structure of a given discrete structure. In addition, there are search algorithms, mostly probabilistic, that are designed for the prospective quantum computer. This book demonstrates the wide applicability of search algorithms for the purpose of developing useful and practical solutions to problems that arise in a variety of problem domains. Although it is targeted to a wide group of readers: researchers, graduate students, and practitioners, it does not offer an exhaustive coverage of search algorithms and applications. The chapters are organized into three parts: Population-based and quantum search algorithms, Search algorithms for image and video processing, and Search algorithms for engineering applications.

4 PATHS ARE HERE
1.A,B,C,F,H,I
2.A,B,G,I
3.A,D,C,F,H,I
4.A,D,E,F,H,I


RESULTANT PAth
1.2+3+3+2+3=13
2.2+1+3=6
3.3+3+3+2+3=14
4.3+1+1+2+3=10