Mathematical Models of Meaning : A Dynamic Systems Approach to Possible World Semiotics.

Format:

Book

Author/Creator:

Kockelman, Paul.

Language:

English

Subjects (All):

Semiotics.

Artificial intelligence.

Physical Description:

1 online resource (215 pages)

Edition:

1st ed.

Place of Publication:

Cambridge : MIT Press, 2025.

Summary:

This book explores the application of mathematical and dynamic systems theories to the study of semiotics, the science of signs and meaning. It examines how entities, or agents, that think, evolve, and learn use signs to interact with their environments. The work delves into topics such as reinforcement learning, biosemiotics, machine learning, and possible world semantics, providing a rigorous framework for analyzing meaning, information, and value. The author integrates concepts from system theory, linguistics, and evolutionary biology to present a multidisciplinary perspective. It is intended for researchers, academics, and students in semiotics, linguistics, artificial intelligence, and related fields. Generated by AI.

Contents:

Cover

Title Page

Copyright

Dedication

Contents

List of Figures

Preface

Acknowledgments

1. Introduction

1.1. The Core Components

1.2. The Main Equation

1.3. Agents That Evolve and Learn

1.4. Signers, Interpreters, and Signals

1.5. Meaning, Information, and Value

1.6. Overview of the Chapters

1.7. Relevant Literature

I. Agents That Think

2. Symptoms and Sickness

2.1. Grounding the Scenario

2.2. Finding the Posteriors

2.3. The Value of the Interpretants

2.4. Calculating the Critical Price

2.5. The Value of a Sign

2.6. The Information in a Sign

2.7. Better and Worse Grounds

3. Predators and Prey

3.1. The Grounds of Predation

3.2. From the Perspective of the Prey

3.3. Predation as Conversation

3.4. Two-Dimensional Dynamics Generated by AI.

Notes:

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

ISBN:

0-262-38348-9

0-262-38349-7

OCLC:

1530377196