College Guide

CS8691 ARTIFICIAL INTELLIGENCE ANNA UNIVERSITY SYLLABUS REGULATION 2017

CS8691 ARTIFICIAL INTELLIGENCE L T P C 3 0 0 3

OBJECTIVES:
 To understand the various characteristics of Intelligent agents
 To learn the different search strategies in AI
 To learn to represent knowledge in solving AI problems
 To understand the different ways of designing software agents
 To know about the various applications of AI.

UNIT I INTRODUCTION 9
Introduction–Definition – Future of Artificial Intelligence – Characteristics of Intelligent Agents– Typical Intelligent Agents – Problem Solving Approach to Typical AI problems.

UNIT II PROBLEM SOLVING METHODS 9
Problem solving Methods – Search Strategies- Uninformed – Informed – Heuristics – Local Search Algorithms and Optimization Problems – Searching with Partial Observations – Constraint Satisfaction Problems – Constraint Propagation – Backtracking Search – Game Playing – Optimal Decisions in Games – Alpha – Beta Pruning – Stochastic Games

UNIT III KNOWLEDGE REPRESENTATION 9
First Order Predicate Logic – Prolog Programming – Unification – Forward Chaining-Backward Chaining – Resolution – Knowledge Representation – Ontological Engineering – Categories and Objects – Events – Mental Events and Mental Objects – Reasoning Systems for Categories – Reasoning with Default Information

UNIT IV SOFTWARE AGENTS 9
Architecture for Intelligent Agents – Agent communication – Negotiation and Bargaining – Argumentation among Agents – Trust and Reputation in Multi-agent systems.

UNIT V APPLICATIONS 9
AI applications – Language Models – Information Retrieval- Information Extraction – Natural Language Processing – Machine Translation – Speech Recognition – Robot – Hardware – Perception – Planning – Moving
TOTAL :45 PERIODS

OUTCOMES:
Upon completion of the course, the students will be able to:
 Use appropriate search algorithms for any AI problem
 Represent a problem using first order and predicate logic
 Provide the apt agent strategy to solve a given problem
 Design software agents to solve a problem
 Design applications for NLP that use Artificial Intelligence.

TEXT BOOKS:
1 S. Russell and P. Norvig, “Artificial Intelligence: A Modern Approach”, Prentice Hall, Third Edition, 2009.
2 I. Bratko, “Prolog: Programming for Artificial Intelligence”, Fourth edition, Addison-Wesley Educational Publishers Inc., 2011.

REFERENCES:
1. M. Tim Jones, “Artificial Intelligence: A Systems Approach(Computer Science)”, Jones
and Bartlett Publishers, Inc.; First Edition, 2008
2. Nils J. Nilsson, “The Quest for Artificial Intelligence”, Cambridge University Press, 2009.
3. William F. Clocksin and Christopher S. Mellish,” Programming in Prolog: Using the ISO Standard”, Fifth Edition, Springer, 2003.
4. Gerhard Weiss, “Multi Agent Systems”, Second Edition, MIT Press, 2013.
5. David L. Poole and Alan K. Mackworth, “Artificial Intelligence: Foundations of Computational Agents”, Cambridge University Press, 2010.

CS8691 ARTIFICIAL INTELLIGENCE R2017 ANNA UNIVERSITY QUESTION PAPER APRIL/MAY 2024 – CLICK HERE