Description

Course Code:CSE422
Course Name: Artificial Intelligence Prerequisite: CSE111, CSE221

Lab 03 Genetic Algorithm
I. Lab Overview:
The students will solve N-Queen problem using python programming and visualizing the evolution performance.
II. Learning Objective:
a. Introducing the 4-Queen problem
b. Solution of 4-Queen problem in Backtracking approach
c. Demerits of Backtracking approach
d. Introducing 8-Queen problem
e. Discussion on Genetic Algorithm
f. Solution of 8-Queen problem using GA
III. Lesson Fit:
There is pre-requisite to this lab: CSE111, CSE221. You should have intensive Programming Knowledge and capability to understand algorithms.
IV. Acceptance and Evaluation
Students will show the output using different datasets and python code. They will be marked according to their lab performance. The main evaluation criteria will be based on
project report and demonstration.

V. Learning Outcome:
After this lab, the students will be able to:
g. Demerits to solve N-Queen problem using Backtracking approach.
h. Solve the N-Queen problem using Genetic Algorithm
VI. Activity Detail
Hour: 1.0 – 2.0

Hour: 2.0-3.0
(It is Not a Group Task, Try Individually)
Marks: 10 Time: 50 minutes Task 1: Implement N-Queen problem using Genetic Algorithm in python programming.
Task 2: Visualize the evolution through plotting the changes of fitness values, and the variances of fitness values for convergence.
Hints: Take help from Prateek Joshi’s Book chapter 8, you can follow Covariance Matrix Adaptation Evolution Strategy (CMA-ES).
—End—
Page of