Assignment No. 02
CS607: Artificial Intelligence
Total Marks: 20
Due Date: 08/05/2013
Please read the following instructions carefully before submitting assignment:
It should be clear that your assignment will not get any credit if:
The objective of this assignment is to enhance your knowledge about;
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.
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.
(Sample search is just given as an example to show how you need to fill this table with desired values.)
You are required to submit your solution in MS Word format through LMS.
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for resultant path no.2 isn't it:
as In ASSIGNMENT GRaph the distance from G - I =13
Please correct me if I'm wrong
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how you find this? please explain.
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Please Discuss here about this assignment.Thanks
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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.
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