Ai Course Outline

Faculty:

GIFT School of Computing Science

Credit hours:

3 

Course level:

Undergraduate

Campus/Location/Instruction Mode:

GIFT University/On Campus/In Person

Course Convenor:

Qamar Askari

Consultation hours:

TBD

Pre-requisite:

Analysis of Algorithm

Timing

Please see the timetable

This document was last updated:

27th Oct, 2018

Topic

Recourse

Week

Introduction to AI

• Definition
• Intelligent Agents and environments
• Application areas and applications

Chap 1,2 & handout/internet reference

Week – 1

Problem solving, Games & Searching

• Problem formulation & example problems
• Uninformed and informed searches

• BFS, DFS, DLS, ID and bidirectional search
• BFS, Branch and bound, A* search

• Local & global search

• Hill climbing, beam search, simulated annealing

• Adversarial search

• Minimax search,  α-β pruning, games with element of chance, 3 player game

Chap 3,4 & 5

Week 2-5

Optimization & Metaheuristics

• Introduction and example problems
• Exact algorithms
• Approximate algorithms/Metaheuristics

• Genetic Algorithm
• Introduction to PSO/ACO etc.

Extra resource

Week 6-7

Midterm

Week 8

Learning

• Supervised learning

• Regression/Neural networks

• Unsupervised learning

• K-means algorithm

• Introduction to reinforcement learning

Extra Resource

Week 8-10

Knowledge representation, logic & reasoning

• Types of knowledge
• Knowledge representations

• Propositional logic
• First order logic

• Reasoning
• Expert Systems
• Prolog
• Uncertain reasoning

• Probability basics
• Naïve Bayes rule and its use
• Statistical learning using Naïve Bayes

Chap 7,8, 9 and 13

Week 10-13

Application areas

• Computer vision

• Segmentation & recognition

• Information retrieval

• Clustering and classification

• Gaming

• Move planning etc.

• Robotics

• Motion & path planning

A brief introduction to above areas and application of AI in above areas will be talked about.

Extra Resource

Week 14

Project evaluation

Week 15-16