JNTUK R19 3-1 Artificial Intelligence Material/Notes PDF Download

Students those who are studying JNTUK R19 CSE Branch, Can Download Unit wise R19 3-1 Artificial Intelligence Material/Notes PDFs below.

JNTUK R19 3-1 Artificial Intelligence Material/Notes PDF Download

Course Objectives: The main objectives are

• To have a basic proficiency in a traditional AI language including an ability to write simple to intermediate programs and an ability to understand code written in that language
• To have an understanding of the basic issues of knowledge representation and blind and heuristic search, as well as an understanding of other topics such as minimax, resolution, etc. that play an important role in AI programs
• To have a basic understanding of some of the more advanced topics of AI such as learning, natural language processing, agents and robotics, expert systems, and planning

Course Outcomes: At the end of the course, the students will be able to:

• Outline problems that are amenable to solution by AI methods, and which AI methods may be suited to solving a given problem
• Apply the language/framework of different AI methods for a given problem
• Implement basic AI algorithms- standard search algorithms or dynamic programming
• Design and carry out an empirical evaluation of different algorithms on problem formalization, and state the conclusions that the evaluation supports

UNIT-1

Introduction, history, intelligent systems, foundations of AI, applications, tic-tac-toe game playing, development of AI languages, current trends.

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UNIT-2

Problem solving: state-space search and control strategies: Introduction, general problem solving, characteristics of problem, exhaustive searches, heuristic search techniques, iterative deepening A*, constraint satisfaction.

Problem reduction and game playing: Introduction, problem reduction, game playing, alpha beta pruning, two-player perfect information games.

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UNIT-3

Logic concepts: Introduction, propositional calculus, proportional logic, natural deduction system, axiomatic system, semantic tableau system in proportional logic, resolution refutation in proportional logic, predicate logic.

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UNIT-4

Knowledge representation: Introduction, approaches to knowledge representation, knowledge representation using semantic network, extended semantic networks for KR, knowledge representation using frames. Advanced knowledge representation techniques: Introduction, conceptual dependency theory, script structure, CYC theory, case grammars, semantic web

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UNIT-5

Expert system and applications: Introduction phases in building expert systems, expert system versus traditional systems

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Uncertainty measure: probability theory: Introduction, probability theory, Bayesian belief networks, certainty factor theory, dempster-shafer theory Fuzzy sets and fuzzy logic: Introduction, fuzzy sets, fuzzy set operations, types of membership functions, multi valued logic, fuzzy logic, linguistic variables and hedges, fuzzy propositions, inference rules for fuzzy propositions, fuzzy systems.

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TEXT BOOKS:

1) Artificial Intelligence- Saroj Kaushik, CENGAGE Learning

2) Artificial intelligence, A modern Approach , 2nded, Stuart Russel, Peter Norvig, PEA

REFERENCE BOOKS:

1) Artificial Intelligence- Deepak Khemani, TMH, 2013

2) Introduction to Artificial Intelligence, Patterson, PHI

3) Atificial intelligence, structures and Strategies for Complex problem solving, -George F Lugar, 5thed, PEA

e-Resources:

1) https://nptel.ac.in

2) http://aima.cs.berkeley.edu/

JNTUK R19 3-1 Compiler Design Material/Notes PDF Download

Students those who are studying JNTUK R19 CSE Branch, Can Download Unit wise R19 3-1 Compiler Design Material/Notes PDFs below.

JNTUK R19 3-1 Compiler Design Material/Notes PDF Download

OBJECTIVES:

• To study the various phases in the design of a compiler
• To understand the design of top-down and bottom-up parsers
• To understand syntax directed translation schemes
• To introduce LEX and YACC tools
• To learn to develop algorithms to generate code for a target machine

Course Outcomes: At the end of the course, the students will be able to:

• Design, develop, and implement a compiler for any language
• Use LEX and YACC tools for developing a scanner and a parser
• Design and implement LL and LR parsers
• Design algorithms to perform code optimization in order to improve the performance of a program in terms of space and time complexity
• Apply algorithms to generate machine code

UNIT-1

Language Processors, the structure of a compiler, the science of building a compiler, programming language basics.

Lexical Analysis: The Role of the Lexical Analyzer, Input Buffering, Recognition of Tokens, The Lexical-Analyzer Generator Lex, Finite Automata, From Regular Expressions to Automata, Design of a Lexical-Analyzer Generator, Optimization of DFA-Based Pattern Matchers.

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UNIT-2

Syntax Analysis: Introduction, Context-Free Grammars, Writing a Grammar, Top-Down Parsing, Recursive and Non recursive top down parsers, Bottom-Up Parsing, Introduction to LR Parsing: Simple LR, More Powerful LR Parsers, Using Ambiguous Grammars, Parser Generators.

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UNIT-3

Syntax-Directed Definitions, Evaluation Orders for SDD’s, Applications of Syntax-Directed Translation, Syntax-Directed Translation Schemes, and Implementing L-Attributed SDD’s.

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Intermediate-Code Generation: Variants of Syntax Trees, Three-Address Code, Types and Declarations, Type Checking, Control Flow, Back patching, Switch-Statements, Intermediate Code for Procedures.

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UNIT-4

Run-Time Environments: Storage organization, Stack Allocation of Space, Access to Nonlocal Data on the Stack, Heap Management, Introduction to Garbage Collection, Introduction to TraceBased Collection.

Machine-Independent Optimizations: The Principal Sources of Optimization, Introduction to Data-Flow Analysis, Foundations of Data-Flow Analysis, Constant Propagation, PartialRedundancy Elimination, Loops in Flow Graphs.

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UNIT-5

Code Generation: Issues in the Design of a Code Generator, The Target Language, Addresses in the Target Code, Basic Blocks and Flow Graphs, Optimization of Basic Blocks, A Simple Code Generator.

Machine-dependent Optimizations: Peephole Optimization, Register Allocation and Assignment, Dynamic Programming Code-Generation.

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TEXT BOOKS:

1. Compilers: Principles, Techniques and Tools, Second Edition, Alfred V. Aho, Monica S. Lam, Ravi Sethi, Jeffry D. Ullman, Pearson.
2. Compiler Construction-Principles and Practice, Kenneth C Louden, Cengage Learning.

REFERENCE BOOKS:

1. Modern compiler implementation in C, Andrew W Appel, Revised edition, Cambridge University Press.
2. The Theory and Practice of Compiler writing, J. P. Tremblay and P. G. Sorenson, TMH
3. Writing compilers and interpreters, R. Mak, 3rd edition, Wiley student edition.

e-Resources:

1) https://nptel.ac.in