This open access book presents an interdisciplinary discussion about symbol emergence systems. From a semiotic perspective, language is one form of symbol. However, the concept of symbol emergence systems refers to a broader notion of symbols those that emerge through shared meaning-making processes across various forms.

This book was written by over twenty researchers from a variety of fields, ranging from artificial intelligence and robotics to linguistics and cognitive science, as well as diverse disciplines in the humanities and social sciences. The book is divided into six parts.

· Part I: Foundations of Symbol Emergence Systems

· Part II: Symbol Emergence in Robotics

· Part III: Cognitive Development in the Environment

· Part IV: Embodiment, Mind, and Consciousness

· Part V: Dynamics of Culture, Norms, and Language

· Part VI: Symbol Emergence Systems and Beyond

With the qualitative transformation triggered by generative AI based on large language models, we have entered a new era in the environment surrounding language. This book will inspire readers to strive for a more panoramic and systemic understanding of symbols and language. The aim is not only to design AI and robots that can engage with language more appropriately, but also to shape a society that can coexist meaningfully with these emerging entities. This book is suitable for anyone interested in such a transdisciplinary approach.

This book is open access, which means that you have free and unlimited access Presents an interdisciplinary discussion about symbol emergence systems Authors' fields range from AI and robotics to various disciplines in the humanities and social sciences Features the discussion about generative AI

Autorentext

Tadahiro Taniguchi is a Professor at the Graduate School of Informatics, Kyoto University, and an Affiliate Professor at the Research Organization of Science and Technology, Ritsumeikan University. He received his Ph.D. in Engineering from Kyoto University in 2006. Over the past two decades, he has made foundational contributions to the interdisciplinary study of cognition, language, and robotics. He proposed the concept of symbol emergence systems, which addresses how symbols arise and evolve through embodied interaction, social communication, and learning. He is also recognized as a pioneer in the field of symbol emergence in robotics, which combines developmental robotics, machine learning, and cognitive science to explore the emergence of meaning and communication in intelligent systems. Taniguchi has authored and edited numerous publications on machine learning, cognitive robotics, emergent communication, and artificial intelligence. He has received multiple academic awards from societies such as the Japanese Society for Artificial Intelligence (JSAI), the Robotics Society of Japan (RSJ), and the Institute of Electronics, Information and Communication Engineers (IEICE). He currently serves as Chair of the IEEE CIS Technical Committee on Cognitive and Developmental Systems, contributing to international leadership in the field.

Inhalt

Chapter 1 Introduction.- Part I: Foundations of Symbol Emergence Systems.- Chapter 2 Symbol Emergence Systems Toward a World Where Humans and AI Co-Discover Meaning.- Chapter 3 Semiotics and Semiology Two Perspectives on Capturing Meaning.- Chapter 4 Pragmatism What Is the Meaning of Symbols?.- Chapter 5 Uexküll's Theory of Umwelt The Worlds as Seen by Living Beings.- Chapter 6 Developmental Psychology and Constructivism: From Piaget to Contemporary Theory.- Chapter 7 Neo-Cybernetics and Information What Is Information?.- Part II: Symbol Emergence in Robotics.- Chapter 8 Symbol Emergence in Robotics A Constructive Approach to Overcoming the Symbol Grounding Problem.- Chapter 9 Language Acquisition Statistical Learning and Social Cognitive Skills.- Chapter 10 Vocabulary Acquisition by Robots Modeling Vocabulary Learning Using Probabilistic Generative Models.- Chapter 11 Probabilistic Generative Models Foundational Theory for Cognitive Modeling Based on Bayesian Inference.- Chapter 12 Multimodal Object Concept Formation Concept Modeling Based on Probabilistic Models.- Chapter 13 Multimodal Spatial Concept Formation Spatial Cognition and Semantics for Mobile Robots.- Part III: Cognitive Development in the Environment.- Chapter 14 Cognitive Developmental Robotics A Constructive Approach to Understanding and Designing Cognitive Development.- Chapter 15 Free-Energy Principle and Predictive Coding A Computational TheoryExplaining Various Brain Functions.- Chapter 16 Curiosity and Exploration Why Do We Want to Learn?.- Chapter 17 Emotion and Predictive Processing How Are Emotions Made?.- Chapter 18 Neurorobotics Controlling Robots with Neural Systems.- Chapter 19 Deep Learning and Representation Learning Foundational Theories Underpinning Modern AI.- Chapter 20 World Models Agents That Learn About the World from Subjective Experience.- Part IV: Embodiment, Mind, and Consciousness.- Chapter 21 Embodiment and the Emergence of Intelligence From Embodied Cognitive Science to Soft Robotics.- Chapter 22 EnactivismCognition as Non-representational, Embodied Action.- Chapter 23 Phenomenology Philosophical Thinking Based on Appearance and Experience.- Chapter 24 Consciousness and Qualia How Do Consciousness and Symbols Relate?.- Chapter 25 AI Robot Society Coexisting with Robots Using Symbols.- Part V: Dynamics of Culture, Norms, and Language.- Chapter 26 Cultural Psychology and Semiosphere Capturing the Tension Between Micro and Macro.- Chapter 27 The Evolution and Emergence of Language How Did Humans Acquire Language?.- Chapter 28 Large Language Models and Distributional Semantics Do Large Language Models Understand Language?.- Chapter 29 Multimodal Language Education Pragmatic Interaction with the Environment.- Chapter 30 Emerging EthicsThe Future of Ethics from the Symbol Emergence Systems Perspective.- Chapter 31 The Legal System and Symbol Emergence The Reciprocal Relationship Between Humans and Symbols.- Part VI: Symbol Emergence Systems and Beyond.- Chapter 32 Language in the Era of Generative AI Insights from Large Language Models.- Chapter 33 Constructive Approaches to Symbol Emergence Systems Probabilistic Generative Models and Language Games.- Chapter 34 The Collective Predictive Coding Hypothesis If Language Exists to Help Us Predict the World.- Chapter 35 Three-Layered Model of Social Intelligence Collective Intelligence in Symbol Emergence Systems and Temporal Dynamics.- Chapter 36 Toward a Symbiotic Society with Generative AI For Living Together into the Future.