Need Help?   +91-638 163 3524 (10AM - 7PM)

Book Details

ARTIFICIAL INTELLIGENCE

ARTIFICIAL INTELLIGENCE

Published by uLektz

Course Code:PCS3D001

Author:uLektz

University: Biju Patnaik University of Technology (BPUT)

Regulation:2016

Categories:Computer Science

Format : ico_bookePUB3 (DRM Protected)

Type :eBook

Rs.224 Rs.179 Rs.20% off

Preview Buy Now

Note : No printed book. Only ebook. Access eBook using uLektz apps for Android, iOS and Windows Desktop PC.

Topics
UNIT - I ARTIFICIAL INTELLIGENCE

1.1 What is Artificial Intelligence?, AI Technique, Level of the Model

1.2 Problem Spaces and Search, Defining the Problem as a State Space Search

1.3 Production Systems, Problem Characteristics, Production System Characteristics, Issues in the Design of Search programs

1.4 Heuristic Search Techniques, Generate-and-Test, Hill Climbing, Best-first Search, Problem Reduction, Constraint Satisfaction, Means-ends Analysis

1.5 Knowledge Representation: Representations and Mappings, Approaches to Knowledge Representation, Using Predicate Logic: Representing Simple Facts in Logic, Representing Instance and ISA Relationships, Computable Functions and Predicates, Resolution, Natural Deduction.

1.6 Using Rules: Procedural Versus Declarative, Logic Programming, Forward Versus Backward Reasoning, Matching, Control Knowledge

1.7 Symbolic Reasoning Under Uncertainty: Introduction to Non-monotonic Reasoning, Logics for Non-monotonic Reasoning, Implementation Issues, Augmenting a Problem-solver, Depth-first Search Breadth-first Search

1.8 Weak and Strong Slot-and-Filler Structures: Semantic Nets, Frames, Conceptual Dependency Scripts, CYC

UNIT - II GAME PLAYING, PLANNING, UNDERSTANDING AND NATURAL LANGUAGE PROCESSING

2.1 Game Playing: The Minimax Search Procedure, Adding Alpha-beta Cutoffs, Iterative Deepening

2.2 Planning: The Blocks World, Components of a Planning System, Goal Stack, Nonlinear Planning Using Constraint Posting, Hierarchical Planning, Other Planning Techniques

2.3 Understanding: What is Understanding, What Makes Understanding Hard?, Understanding as Constraint Satisfaction

2.4 Natural Language Processing: Introduction, Syntactic Processing, Semantic Analysis, Discourse and Pragmatic Processing, Statistical Natural Language Processing, Spell Checking

UNIT - III LEARNING AND EXPERT SYSTEMS

3.1 Learning: Rote Learning, Learning by Taking Advice, Learning in Problem-solving, Learning from Examples: Induction

3.2 Explanation-based, Discovery, Analogy, Formal Learning Theory, Neural Net Learning and Genetic Learning

3.3 Expert Systems: Representing and Using Domain Knowledge

3.4 Expert System Shells-Explanation, Knowledge Acquisition

loading