NIT Raipur Syllabus 7th Sem Information Technology Branch

NIT-RAIPUR

VII SEM Information Technology SYLLABUS

 

SEMESTER – VII

Management Information System

Theory Periods: 30 Tutorials: “10”

Credits: 4 Code: IT 701

 

UNIT – I: MANAGEMENT & ORGANIZATIONAL SUPPORT SYSTEMS FOR DIGITAL FIRM

 

Definition of MIS; Systems approach to MIS: MIS and Human factor considerations, concept of

organizational information sub-system, MIS & problem solving. Information Technology

Infrastructure for digital firm. Related Case Studies.

 

UNIT – II: INFORMATION SYSTEMS & BUSINESS STRATEGY

 

Information Management. Who are the users? Managers, Decision making & information System,

Evolution of Computer based information system (CBIS), Model of CBIS. Changing role of

Information systems in organization: Trend to End-User computing, justifying the CBIS, Achieving

the CBIS, Managing the CBIS, Benefits & Challenges of

CBIS implementation. Strategic Information System, Business level & Firm level Strategy, Case

Studies.

 

UNIT – III: INFORMATION SYSTEMS IN THE ENTERPRISE

 

Systems from Management & Functional perspective & their relationship: Executive Support System,

Decision Support System, Sales & Marketing Information System, Manufacturing Information

System, Human-Resource Information System. Finance & Account Information System. Case Studies.

 

UNIT – IV: INFORMATION TECHNOLOGY FOR COMPETITIVE ADVANTAGE:

 

Firm in its environment, the information resources, who manages the information resources?

Strategic planning for information resources. End-User Computing as a strategic issue, Information

resource management concept. Knowledge management & their work system, Business value of

information system Related Case Studies.

 

UNIT – V: INTERNATIONAL INFORMATION SYSTEM:

 

Managing International Information Systems: IIS architecture, Global business drivers, challenges,

and strategy: divide, conquer, appease, cooptation, business organization, problems in implementing

global information systems,

Understanding ethical and social issues related to systems, ethics in information society, and Moral

dimensions of information systems.

 

Name of Text Books:

 

1. MIS managing the digital firm, Kenneth C. Laudon & Jane P. Laudon (Pearson Education).

2. MIS, Suresh K. Basandra (Wheelers).

 

Name of Reference Books:

 

1. Introduction to computer Information System for Business, Mark G. Simkin. S. Chand & Co.,

1996.

2. Analysis & Design of Information Systems, James A. Senn. MC Graw-Hill International

edition, 1989.

3.

Analysis and Design of information system , V.Rajaraman(PHI)

NATIONAL INSTITUTE OF TECHNOLOGY, RAIPUR, CG 492010

Department of Information Technology

 

SEMESTER – VII

 

 

 

Artificial Intelligence and Expert Systems

Theory Periods: 40 Tutorials: “10”

Credits: 5 Code: IT 702

 

UNIT-I: GENERAL ISSUES AND OVERVIEW OF AI

 

The AI problems; what is an AI technique; Level of model, criteria for success, Characteristics of AI

applications, Problem Solving, State Space Search, Production systems, Control strategies: forward

and backward chaining, Problem characteristics, Production System characteristics, issues in the

design of search program, Data driven and goal driven search, Exhaustive searches: Depth first &

Breadth first search.

 

UNIT-II: HEURISTIC SEARCH TECHNIQUES

 

Heuristics & Heuristic function, Heuristic Search – Generate & test, Hill climbing; Branch and Bound

technique; Best first search & A* algorithm; AND/OR Graphs; Problem reduction and AO* algorithm;

Constraint Satisfaction problems, Means End Analysis.

 

UNIT-III: KNOWLEDGE REPRESENTATION

 

Introduction to knowledge representation-Propositional calculus, First Order Predicate Calculus,

conversion to clause form, Unification ,Theorem proving by Resolution, Natural Deduction ,Inference

Mechanisms Horn’s Clauses; Knowledge representation issues-Representation and mapping,

Approaches to Knowledge representation, Frame Problem, Structured knowledge representation-

Semantic Networks Frame representation and Value Inheritance; Conceptual Dependency and

Scripts. Introduction to Agent based problem solving.

 

UNIT-IV: REASONING UNDER UNCERTAINITY & APPLICATIONS OF AI

 

Source of Uncertainty, Probabilistic Reasoning and Uncertainty; Probability theory; Bayes Theorem

and Bayesian networks, Certainty Factor, Dempster-Shafer theory, Non Monotonic Reasoning, Truth

maintenance Systems, Overview of Fuzzy Logic.

 

Natural language processing:

 

overview, Basic steps followed for the NLP, concept of NLP, Parsing,

machine translation,

Planning Overview – An Example Domain: The Blocks Word; Component of

Planning Systems; Goal Stack Planning (linear planning); Non-linear Planning using constraint

posting.

Learning, Rote Learning; Learning by Induction, Learning in Problem Solving, Explanation

based learning and Discovery.

 

UNIT-V: GAME PLAYING, AI Languages & EXPERT SYSTEMS

 

Game Playing Minmax search procedure; Alpha-Beta cut-offs; Additional Refinements, AI

Programming Languages: Introduction to LISP and PROLOG, Syntax and Numeric Functions; List

manipulation functions, programming in Lisp/Prolog, Iteration and Recursion. Introduction to

Expert Systems, characteristics, Architecture of Expert Systems, Development of Expert System,

Software Engineering and Expert System, Expert System Life Cycle model, Expert System Shells;

Knowledge Acquisition; Case Studies: MYCIN,

 

Name of Text Books:

 

1.

 

Elaine Rich and Kevin Knight: Artificial Intelligence- Tata McGraw Hill.

 

2.

 

Dan W.Patterson, Introduction to Artificial Intelligence and Expert Systems- Prentice Hall of

India.

 

3.

 

Joseph C Giarratano, Gary D Riley: Expert System Principles & Programming, 4th Edition.

 

Name of Reference Books:

 

1.

 

Nils J.Nilsson: Principles of Artificial Intelligence- Narosa Publishing house.

 

2.

 

Artificial Intelligence: A Modern Approach, Stuart Rusell, Peter Norvig, Pearson Education,

2

nd Edition.

 

3.

 

Artificial Intelligence, Winston, Patrick, Henry, Pearson Education.

 

4.

 

Artificial Intelligenece by Gopal Krishna , Janakiraman.

NATIONAL INSTITUTE OF TECHNOLOGY, RAIPUR, CG 492010

Department of Information Technology

 

SEMESTER – VII

 

 

 

Digital Image Processing

Theory Periods: 30 Tutorials: “10”

Credits: 4 Code: IT 703

 

Unit I: Introduction

 

Image formation model, Spatial & Gray level resolution, Image enhancement in special domain:

Piecewise transformation functions, Histogram equalization, Histogram specification, image

averaging, spatial filters- smoothing and sharpening, Laplacian filter, Canny edge detector.

 

Unit II: Image enhancement in frequency domain & Image Segmentation

 

2D discrete fourier transform & its inverse, filtering in frequency domain, Ideal & Gaussian low pass

filters, High pass filtering, FFT, Line detection, Edge detection, Edge linking & boundary detection,

Thresholding, Region based segmentation.

 

Unit III: Morphological Image Processing

 

Logic operations involving binary image, Dialation & Erosion, Opening & Closing, Applications to

Boundary extraction, region filling, connected component extraction.

 

Unit IV: Image Compression:

 

Coding redundancy- Huffman coding, LZW coding, run length coding, Lossy compression- DCT,

JPEG, MPEG, video compression.

 

Unit V: Image Representation & 3D:

 

Boundary descriptors, Shape numbers, Texture, Projective geometry, Correlation based and feature

based stereo correspondence, shape from motion, optical flow.

 

Name of Text Books:

 

1.

 

Ganzalez and Woods, Digital Image Processing, Pearson education.

 

2.

 

Sonka and Brooks, Image Processing, TSP ltd,

 

Name of Reference Books:

 

1.

 

Jain and Rangachar, Machine Vision, MGH.

 

2.

 

Schalkoff, Digital Image Processing, John Wiley and sons.

NATIONAL INSTITUTE OF TECHNOLOGY, RAIPUR, CG 492010

Department of Information Technology

 

SEMESTER – VII

 

 

 

Advanced Computer Architecture

Theory Periods: 30 Tutorials: “10”

Credits: 4 Code: IT 704

 

Unit – I: Introduction

 

Parallel Computing, Parallel Computer Model, Program and Network Properties, Parallel

Architectural Classification Schemes, Flynn’s & Feng’s Classification, Performance Metrics and

Measures, Speedup Performance Laws: Multiprocessor System and Interconnection Networks; IEEE

POSIX Threads: Creating and Exiting Threads, Simultaneous Execution of Threads, Thread

Synchronization using Semaphore and Mutex, Canceling the Threads.

 

Unit – II: Pipelining and Memory Hierarchy

 

Basic and Intermediate Concepts, Instruction Set Principle; ILP: Basics, Exploiting ILP, Limits on ILP;

Linear and Nonlinear Pipeline Processors; Super Scalar and Super Pipeline Design; Memory

Hierarchy Design: Advanced Optimization of Cache Performance, Memory Technology and

Optimization, Cache Coherence and Synchronization Mechanisms.

 

Unit – III: Thread and Process Level Parallel Architecture

 

Introduction to MIMD Architecture, Multithreaded Architectures, Distributed Memory MIMD

Architectures, Shared Memory MIMD Architecture, Clustering, Instruction Level Data Parallel

Architecture, SIMD Architecture, Fine Grained and Coarse Grained SIMD Architecture, Associative

and Neural Architecture, Data Parallel Pipelined and Systolic Architectures, Vector Architectures.

 

Unit – IV: Parallel Algorithms

 

PRAM Algorithms: Parallel Reduction, Prefix Sums, Preorder Tree Traversal, Merging two Sorted

lists; Matrix Multiplication: Row Column Oriented Algorithms, Block Oriented Algorithms; Parallel

Quicksort, Hyper Quicksort; Solving Linear Systems: Gaussian Elimination, Jacobi Algorithm;

Parallel Algorithm Design Strategies.

 

Unit –V: Developing Parallel Computing Applications

 

OpenMP Implementation in ‘C’: Execution Model, Memory Model; Directives: Conditional

Compilation, Internal Control Variables, Parallel Construct, Work Sharing Constructs, Combined

Parallel Work-Sharing Constructs, Master and Synchronization Constructs; Run-Time Library

Routines: Execution Environment Routines, Lock Routines, Timing Routines; Simple Examples in ‘C’.

Basics of MPI.

 

Name of Text Books:

 

1.

 

Kai Hwang,” Advance Computer Architecture”, TMH.

 

2.

 

Matthew, ”Beginning Linux Programming”, SPD/WROX.

 

3.

 

Hennessy and Patterson,” Computer Architecture: A Quantitative Approach”, Elsevier.

 

4.

 

Dezso and Sima, ”Advanced Computer Architecture”, Pearson.

 

5.

 

Quinn, “Parallel Computing: Theory & Practice”, TMH.

 

6.

 

Quinn, “Parallel Programming in C with MPI and Open MP”, TMH Open MP Specification

and Usage

NATIONAL INSTITUTE OF TECHNOLOGY, RAIPUR, CG 492010

Department of Information Technology

 

SEMESTER – VII

 

 

 

Fault Tolerant System

Theory Periods: 30 Tutorials: “10”

Credits: 4 Code: IT 705

 

UNIT – I

 

Fundamental Concepts:

 

Definitions of fault tolerance, fault classification, fault tolerant attributes and

system structure.

 

Fault-Tolerant Design Techniques:

 

Information redundancy, hardware redundancy, and time

redundancy.

 

UNIT-II

 

Dependability Evaluation Techniques:

 

Reliability and availability models: (Combinatorial

techniques, Fault-Tree models, Markov models), Performability Models.

 

Architecture of Fault-Tolerant Computers (case study):

 

General-purpose systems, high-availability

systems, long-life systems, critical systems.

 

UNIT – III

 

Software Fault Tolerance:

 

Software faults and their manifestation, design techniques, reliability

models.

 

UNIT – IV

 

Fault Tolerant Parallel/Distributed Architectures:

 

Shared bus and shared memory architectures,

fault tolerant networks.

 

UNIT – V

 

Recent topics in fault tolerant systems:

 

Security, fault tolerance in wireless/mobile networks and

Internet.

 

Name of Text Books:

 

1.

 

Fault-Tolerant Computer System Design D.K. Pradhan, 2003

 

2.

 

Design and Analysis of Fault-Tolerant Digital Systems B.W.Johnson, Addison-Wesley, 1989

 

3.

 

Fault-Tolerant Computing, Theory and Techniques, Volumes I and II D.K. Pradhan, Prentice

Hall, 1986

 

4.

 

Reliable Computer Systems: Design and Evaluation D.P.Siewiorek and R.S.Swartz, Digital

Press, 1992

 

5.

 

Probability and Statistics with Reliability, Queueing and Computer Science Application

K.S.Trivedi, Prentice Hall, 1982

NATIONAL INSTITUTE OF TECHNOLOGY, RAIPUR, CG 492010

Department of Information Technology

 

SEMESTER – VII

 

 

 

Decision Support System

Theory Periods: 30 Tutorials: “10”

Credits: 4 Code: IT 706

 

Unit-I

 

Strategic, tactical and operational. Consideration of organizational structures. Mapping of databases,

MIS, EIS, KBS, expert systems, OR modeling systems and simulation, decision analytic systems onto

activities within an organization. Extension to other ‘non organizational’ areas of decision making.

Relationship withknowledge management systems

 

Unit-II

 

Studies of human cognition in relation to decision making and the assimilation of information.

Cultural issues. Implications for design of decision-making support. Communication issues.

 

Unit -III

 

Normative, descriptive and prescriptive analysis: requisite modeling. Contrast with recognition

primed decision tools.

 

Unit -IV

 

Database, MIS, EIS, KBS, Belief nets, data mining. OR modeling tools: simulation and optimization.

History, design, implementation: benefits and pitfalls. Risk assessment, Decision analysis and

strategic decision support.

 

Unit -V

 

Group decision support systems and decision conferencing. Intelligent decision support systems:

tools and applications. Cutting-edge decision support technologies. History, design, implementation:

benefits and pitfalls. Deliberative e-democracy and e-participation

 

Name of Text Books:

 

1. P.R. Kleindorfer, H.C. Kunreuther, P.J.H. Schoemaker “Decision Sciences: an integration

perspective’ Cambridge University Press 1993

1. G.M. Marakas, Decision support Systems in the 21st Century, Prentice Hall, 1999.

 

Name of Reference Books:

 

1. E. Turban and J.E. Aronson (2001) Decision support Systems and Intelligent Systems. 6

th

Edition. PHI

2. V.S.Janakiraman and K.Sarukesi, Decision Support Systems, PHI

3. Efrem G. Mallach, Decision Support and Data Warehouse Systems, tata McGraw-Hill Edition

NATIONAL INSTITUTE OF TECHNOLOGY, RAIPUR, CG 492010

Department of Information Technology

 

SEMESTER – VII

 

 

 

Natural Language Processing

Theory Periods: 30 Tutorials: “10”

Credits: 4 Code: IT 707

 

Unit – I

 

Introduction to Natural Language Processing, Different Levels of language analysis, Representation

and understanding, Linguistic background.

 

Unit – II

 

Grammars and parsing, Top down and Bottom up parsers, Transition Network Grammars, Feature

systems and augmented grammars, Morphological analysis and the lexicon, Parsing with features,

Augmented Transition Networks.

 

Unit -III

 

Grammars for natural language, Movement phenomenon in language, Handling questions in context free

grammars, Hold mechanisms in ATNs, Gap threading, Human preferences in parsing, Shift reduce parsers,

Deterministic parsers, Statistical methods for Ambiguity resolution

 

Unit – IV

 

Semantic Interpretation, word senses and ambiguity, Basic logical form language, Encoding

ambiguity in logical from, Thematic roles, Linking syntax and semantics, Recent trends in NLP.

 

Unit – V

 

Language Model: the Milton Model , THE META MODEL, Vision for the Future’, Strategies , NLP

Change Techniques ,Principle-based NLP, Reframing , Chunking Patterns

 

Name of Text Books:

 

1.

 

James Allen, Natural Language Understanding, Second Edition, 2003, Pearson Education.

 

2.

 

D Juraffsky, J H Martin, Speech and Language Processing, Pearson Education.

NATIONAL INSTITUTE OF TECHNOLOGY, RAIPUR, CG 492010

Department of Information Technology

 

SEMESTER – VII

 

 

 

Robotics

Theory Periods: 30 Tutorials: “10”

Credits: 4 Code: IT 708

 

Unit- I

 

The scope of industrial robotics – definition of an industrial robot – need for industrial robots,

Applications – fundamentals of robot technology, automation and robotics, robot anatomy, work

volume, precision of movement End effectors, sensors.

 

Unit- II

 

Robot Programming – methods – interlocks textual languages – characteristics of robot level

languages, characteristics of task level languages

 

Unit- III

 

Puma robot Arm Control – Computed Torque Technique – Near minimum time control – Variable

structure control – Non – linear decoupled feedback control – Reserved motion control – Adaptive

control.

 

Unit- IV

 

Robot cell design and control – Remote centre compliance – safety in robotics.

 

Unit- V

 

Advanced robotics, advanced robotics in space – specific features of space robotics systems – long

term technical developments – advanced robotics in underwater operations, Robotics technology for

the future – future applications

 

Name of Text Books:

 

1.

 

Barry Leatham Jones, “ Elements of Industrial Robotics” Pitman Publishing, 1987 .

 

Reference Books

 

1.

 

Mikell P. Groover , Mitchell Weiss, Roger N . Nagel, Nicholas G. Odrey, “Industrial

Technology , Programming and applications” , Mc Graw Hill Book Company, 1986

 

2.

 

Fu K.S. , Gonzalez R.C. and Lee C.S.G , “Robotics – Control, Sensing , Vision and

applications” , McGraw Hill International Editions , 1987

.

 

3.

 

Bernard Hodges and Paul Hallam, “Industrial Robotics” , British Library Cataloging in

Publication, 1990.

NATIONAL INSTITUTE OF TECHNOLOGY, RAIPUR, CG 492010

Department of Information Technology

 

SEMESTER – VII

 

 

 

Distributed System and Parallel Processing

Theory Periods: 30 Tutorials: “10”

Credits: 4 Code: IT 709

 

UNIT I

 

Concept of Distributed system, Centralized Computing, Advantages of Distributed systems over

centralized system, Examples of Distributed Systems. Architectural model of Distributed Systems,

Centralized Architectures, Decentralized Architecture, Hybrid Architecture, Security in Distributed

Systems. Concept of clock in Distributed System, Limitation of Distributed System, Clock synchronization,

Lamport’s Logical Clock, Vector Clocks, Causal ordering of messages- Birman-Schiper Stephen Protocol,

Schiper Eggli Sandoz Protocol, Chandy- Lamport’s Global State Recording Algorithm, Termination

Detection Algorithm.

 

UNIT II

 

Distributed Mutual Exclusion, Mutual Exclusion in single computer system Vs Distributed, Concept of

Critical Section, Non Token-based algorithm- Central Coordinator Algorithm, Lamport’s Algorithm,

Ricart-Agrawala Algorithm, Maekawa’s Algorithm, Token based algorithm- Token Ring Algorithm,

Suzuki-kasami’s Broadcast Algorithm, Singhal’s Heuristic Algorithm, Raymonds Tree based Algorithm.

 

Distributed deadlock detection:

 

Control organization- Centralized Vs Distributed, Completely

centralized, The Ho-Ramamoorthy , one-phase algorithm, Distributed- path pushing, edge chasing,

Diffusion computation based, Global state detection based algorithm, Hierarchical – The Menasce-Muntz

Algorithm, The Ho-Ramamoorthy Algorithm, Deadlock Resolution.

 

Agreement protocol:

 

System model, The Byzantine Agreement problem, Solution to the Byzantine

Agreement problem- Lamport Shostak-Pease Algorithm, Dolev et al. algorithm, Applications of

Agreement algorithm- Fault tolerant clock synchronization, Atomic commit.

 

UNIT III

 

Distributed Storage, Name Services, Transaction, Distributed Transaction, Replication, Recovery in

Distributed System, Commit protocol- The Two-Phase commit protocol, Voting Protocol- Static Vs

Dynamic voting.

 

UNIT IV

 

Computational demands, advantages of parallel systems. Flynn’s classification, controlled parallelism and

scalability. Topologies: Mesh, binary tree, Hyper tree, Cube Connected cycles, shuffle-Connected

Exchange; Uniform Memory Access (UMA & Non uniform Memory Access (NUMA) Multi processor

System.PARAM Model of Parallel Computation, PARAM Algorithms; Parallel Reductions, Prefix sum,

List Ranking, Merging of Two Sorted List.

 

UNIT V

 

Algorithm for parallel machine- Parallel Algorithm Introduction, Models of Parallel Computation, Parallel

Prefix Computation, Parallel Merging, Parallel Searching, Parallel Sorting, Matrix Multiplication.

 

Name of Text Books:

 

1. G. Couloris, “Distributed System, Concept & Design,” Addison Wesley 1994.

2. Tanenbaum, “Distributed Systems,” PHI.

3. P. K. Sinha, “Distributed Operating Systems,” PHI.

4. Michel J. Quinn, “ Parallel Computing: Theory and Practice,” McGraw-Hill.

NATIONAL INSTITUTE OF TECHNOLOGY, RAIPUR, CG 492010

Department of Information Technology

 

SEMESTER – VII

 

“Pattern Recognization”

 

Theory Periods: 30 Tutorials: “10

Credits: 4 Code: IT 710

 

UNIT-I INTRODUTION

 

Introduction to statistical – syntactic and descriptive approaches – features and feature extraction –

learning – Bayes Decision theory – introduction – continuous case – 2-category classification –

minimum error rate classification – classifiers – discriminant functions – and decision surfaces – error

probabilities and integrals – normal density – discriminant functions for normal density

 

UNIT-II ESTIMATION AND LEARNING

 

Parameter estimation and supervised learning – maximum likelihood estimation – the Bayes classifier

– learning the mean of a normal density – general bayesian learning – nonparametric technic – density

estimation – parzen windows – k-nearest neighbour estimation – estimation of posterior probabilities –

nearest – neighbour rule – k-nearest neighbour rule

 

UNIT-III FUNCTIONS

 

Linear discriminant functions – linear discriminant functions and decision surfaces – generalized

linear discriminant functions – 2-category linearly separable case – non-separable behavior.

 

UNIT-IV PROGRAMMING PROCEDURES

 

Linear programming procedures – clustering – data description and clustering – similarity measures –

criterion functions for clustering

 

UNIT-V GRAMMAR AND LANGUAGE

 

Syntactic approach to PR – introduction to pattern grammars and languages – higher dimensional

grammars – tree, graph, web, plex, and shape grammars – stochastic grammars – attribute grammars –

parsing techniques – grammatical inference

 

Name of Text Books:

 

1.

 

Duda & Hart P.E, Pattern Classification And Scene Analysis, John Wiley and Sons, NY

 

Name of Reference Books:

 

1.

 

Gonzalez R.C. & Thomson M.G., Syntactic Pattern Recognition – An Introduction, Addison

Wesley

 

2.

 

Fu K.S., Syntactic Pattern Recognition And Applications, Prentice Hall, Englewood cliffs, N.J.

NATIONAL INSTITUTE OF TECHNOLOGY, RAIPUR, CG 492010

Department of Information Technology

 

SEMESTER – VII

 

“Computational Intelligence

 

 

 

Theory Periods: 30 Tutorials: “10”

Credits:4 Code: IT 711

 

UNIT-I

 

Artificial Intelligence: History and Applications, Production Systems, Structures and Strategies for state space

search- Data driven and goal drivensearch, Depth First and Breadth First Search, DFS with Iterative

Deepening,Heuristic Search- Best First Search, A* Algorithm, AO* Algorithm, Constraint Satisfaction, Using

heuristics in games- Minimax Search, Alpha BetaProcedure.

 

UNIT-II

 

Knowledge representation – Propositional calculus, Predicate Calculus, Theorem proving by Resolution,

Answer Extraction, AI Representational Schemes- Semantic Nets,

 

UNIT-III

 

Conceptual Dependency, Scripts, Frames, Introduction to Agent based problem solving. Machine Learning-

Symbol based and Connectionist, Social and Emergent models of learning,

 

UNIT-IV

 

The Genetic Algorithm- Genetic Programming, Overview of Expert System Technology- Rule based Expert

Systems, Introduction to Natural Language Processing.

 

UNIT-V

 

Languages and Programming Techniques for AI- Introduction to PROLOG and LISP, Search strategies and

Logic Programming in LISP, Production System examples in PROLOG.

 

Name of Text Books:

 

1.

 

George F Luger, Artificial Intelligence- Structures and Strategies for Complex Problem Solving, 4/e, 2002,

Pearson Education.

 

Name of Reference Books:

 

1.

 

E. Rich, K.Knight, Artificial Intelligence, 2/e, Tata McGraw Hill

 

2.

 

S Russel, P Norvig, Artificial Intelligence- A Modern Approach, 2/e, Pearson Education, 2002

 

3.

 

Winston. P. H, LISP, Addison Wesley

 

4.

 

Ivan Bratko, Prolog Programming for Artificial Intelligence, 3/e, Addison Wesley, 2000

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