Artificial Intelligence Principles

CS2107 Design & Analysis of Algorithms

3 hours One requisite

1 Intro to AI (Concepts, Domains and Applications)

2 Intelligent Agents and Agent Environment

3 Problem Solving through intelligent search algorithms (Un-informed / Search, Informed Search)

4 Local Search Algorithms (Gradient Descent method, genetic algorithms)

5 Adversarial Search algorithms (Minimax Algorithm, Alpha Beta Pruning, Chance Minimax)

6 Constraint Satisfaction Problem

7 Logical Agents (knowledge-based agents, propositional logic, First Order Logic, Resolution)

1.1 Mapped to: K1

Describe what constitutes "Artificial" Intelligence and how to identify systems with artificial intelligence.

Teaching Strategy Course lectures, tutorials, demonstration, discussion.

Assessment Methods Quizzes, Assignments, Midterm Exam

1.2 Mapped to: K1, K2

Differentiate between AI search algorithms (uninformed, informed, local search, genetic algorithms, constraint satisfaction, adversarial search).

Teaching Strategy Course lectures, tutorials, demonstration, discussion.

Assessment Methods Quizzes, Assignments, Midterm Exam, Final Exam, Project

2.1 Mapped to: S1,S2

Apply Artificial Intelligence techniques for problem solving to real-world problems.

Teaching Strategy Course lectures, tutorials, demonstration, discussion.

Assessment Methods Project, Assignments

3.1 Mapped to: V1

Ensuring AI systems are designed to benefit society.

Teaching Strategy Course lectures, tutorials, demonstration, discussion.

Assessment Methods Project, Assignments

Welcome