Librería Portfolio

Description
Intelligent agents are employed as the central characters in this new introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. The book provides a refreshing and motivating new synthesis of the field by one of AI´s master expositors and leading researchers. Artificial Intelligence: A New Synthesis takes the reader on a complete tour of this intriguing new world of AI.

Key Features
An evolutionary approach provides a unifying theme
Thorough coverage of important AI ideas, old and new
Frequent use of examples and illustrative diagrams
Extensive coverage of machine learning methods throughout the text
Citations to over 500 references
Comprehensive index



Table of Contents
1 Introduction

1.1 What is AI?

1.2 Approaches to Artificial Intelligence

1.3 Brief History of AI

1.4 Plan of the Book

1.5 Additional Readings and Discussion

I Reactive Machines

2 Stimulus-Response Agents

2.1 Perception and Action

2.1.1 Perception

2.1.2 Action

2.1.3 Boolean Algebra

2.1.4 Classes and Forms of Boolean Functions

2.2 Representing and Implementing Action Functions

2.2.1 Production Systems

2.2.2 Networks

2.2.3 The Subsumption Architecture

2.3 Additional Readings and Discussion

3 Neural Networks

3.1 Introduction

3.2 Training Single TLUs

3.2.1 TLU Geometry

3.2.2 Augmented Vectors

3.2.3 Gradient Descent Methods

3.2.4 The Widrow-Hoff Procedure

3.2.5 The Generalized Delta Procedure

3.2.6 The Error-Correction Procedure

3.3 Neural Networks

3.3.1 Motivation

3.3.2 Notation

3.3.3 The Backpropagation Method

3.3.4 Computing Weight Changes in the Final Layer

3.3.5 Computing Changes to the Weights in Intermediate Layers

3.4 Generalization, Accuracy, and Overfitting