Artificial Intelligence using Prolog Programming

Overview

Artificial Intelligence (AI) is an interdisciplinary field that involves the development of intelligent machines and systems that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision making, and natural language processing. Prolog is a programming language that is particularly well-suited for AI applications due to its ability to represent and reason about complex knowledge.This course on Artificial Intelligence using Prolog programming is designed to provide students with an in-depth understanding of the key concepts and techniques of AI, as well as the skills to implement AI solutions using Prolog. The course is divided into several modules, each focusing on a different aspect of AI and Prolog programming.

Syllabus

Week No

Title

Week 1

Introduction to Artificial Intelligence (AI), Problem Solving

State Space Search, – 8 Puzzle Problem

– Water Jug Problem

Week 2

Missionaries and Cannibals Problem

Blind Search: Depth First Search (DFS)

Blind Search: Breadth First Search (BFS)

Informed Search: Heuristic Function, Hill Climbing Search

Week 3

Best First Search

A* Search

AO* Search

Week 4

Constraint Satisfaction

Evaluation Function

Mini-Max Search

Alpha-Beta Pruning

Week 5

Branch and Bound Search

Introduction to KR (Knowledge Representation)

Knowledge Agent

Predicate Logic, WFF, Inference Rules & Theorem Proving, – Forward Chaining ,Backward Chaining

Week 6

Resolution

Propositional Knowledge

Boolean Circuit Agents, Rule-Based Systems

Forward Reasoning: Conflict Resolution, – Backward Reasoning: Use of Backtracking

Week 7

Semantic Net

– Slots, Inheritance

Frames, – Exceptions and Defaults, Attached Predicates

Conceptual Dependency

Week 8

Handling Uncertainty & Learning

Source of Uncertainty

Probabilistic Inference, Bayes’ Theorem

Limitation of Naïve Bayesian System, Dempster-Shafer Theory

Week 9

Learning

Goal Stack Planning

Block World Problem

Week 10

Introduction to Machine Learning (ML) in AI

Supervised Learning

Unsupervised Learning

Reinforcement Learning

Introduction to Natural Language Processing (NLP)

Week 11

Parsing

Machine Translation

Introduction to Expert Systems

Need & Justification for Expert Systems, – Cognitive Problems, Case Studies of Expert Systems

Week 12

Introduction to Prolog Programming, Installation

Facts, Rules, Clauses, and Lists in Prolog

Understanding Logical Operators in Prolog

Prolog Program for Various Relations, List Operations in Prolog, Union and Intersection, Wrap-up Summary of the Course

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