Name: Notes Artificial Intelligence AI
Rating: 3.4 (48 reviews)
Author: Dr. Biswaranjan Nayak

What is Artificial Intelligence? AI Technique, Level of the Model,Problem Spaces, and
Search: Defining the Problem as a State Space Search, Production Systems, Problem
Characteristics, Production System Characteristics, Issues in the Design of Search
Programs.Heuristic Search Techniques: Generate-and-Test, Hill Climbing, Best-first Search,
Problem Reduction, Constraint Satisfaction, Means-ends Analysis,Knowledge

What Is Artificial Intelligence Ai Technique

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.Using Rules: Procedural Versus Declarative Knowledge, Logic Programming,
Forward Versus Backward Reasoning, Matching, Control Knowledge.Symbolic Reasoning
Under Uncertainty: Introduction to Nonmonotonic Reasoning, Logics for Nonmonotonic
Reasoning, Implementation Issues, Augmenting a Problem-solver, Depth-first Search,
Breadth-first Search.Weak and Strong Slot-and-Filler Structures: Semantic Nets, Frames,
Conceptual DependencyScripts, CYC.

Representation Representations And Mappings Approaches To Knowledge

Game Playing: The Minimax Search Procedure, Adding Alpha-beta Cutoffs, Iterative
Deepening.Planning: The Blocks World, Components of a Planning System, Goal Stack
Planning, Nonlinear Planning Using Constraint Posting, Hierarchical PlanningOther
Planning Techniques.Understanding: What is Understanding, What Makes Understanding
Hard?, Understanding as Constraint Satisfaction.

Game Playing Components Of A Planning System

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

Statistical Natural Language Processing Spell Checking

Expert Systems: Representing
and Using Domain Knowledge, Expert System Shells, Explanation, Knowledge Acquisition.

Expert Systems

Learning: Rote Learning, Learning by Taking Advice, Learning in Problem-solving, Learning
from Examples: Induction, Explanation-based Learning, Discovery, Analogy, Formal
Learning Theory, Neural Net Learning and Genetic Learning

Notes for Artificial Intelligence - AI by Dr. Biswaranjan Nayak

BPUT ·

AI