LNAI 2801 Adaptive Coupling and Intersubjectivity in Simulated Turn Taking Behaviour 1st Edition by Hiroyuki Iizuka, Takashi Ikegami ISBN 9783540200574 354020057X

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Product details:
ISBN 10: 354020057X
ISBN 13: 9783540200574
Author: Hiroyuki Iizuka, Takashi Ikegami

Turn-taking behaviour is simulated with a coupled agents system. Each agent is modelled as a mobile robot with two wheels. A recurrent neural network is used to produce the motor outputs and to hold the internal dynamics. Agents are developed to take turns on a two dimensional arena by causing the network structures to evolve.

Turn-taking is established using either regular or chaotic behaviour of the agents. It is found that chaotic turn-takers are more sensitive to the adaptive inputs from the other agent. On the other hand, regular turn-takers are comparatively insensitive to noisy inputs due to their restricted dynamics. From various observations, including turn-taking with virtual agents, we claim that the chaotic turn-taking agents become less robust when coping with virtual agents but at the same time, those agents are more adaptable to each other than the regular turn-taking agents. All these findings are discussed and compared with Trevarthen’s double monitor experiments.

LNAI 2801 Adaptive Coupling and Intersubjectivity in Simulated Turn Taking Behaviour 1st Edition Table of contents:

Chapter 1: Introduction to Turn-Taking Behaviour

• What is Turn-Taking Behaviour?
• The Role of Turn-Taking in Human Communication
• Turn-Taking in Computational Models and Simulations
• Research Questions and Objectives of the Book

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Chapter 2: Theories of Turn-Taking in Human Interaction

• Cognitive and Psychological Foundations of Turn-Taking
• Social and Cultural Aspects of Turn-Taking
• Intersubjectivity in Communication: Shared Understanding and Mutual Attention
• Theoretical Models of Turn-Taking and Their Application

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Chapter 3: Adaptive Coupling in Interaction

• Understanding Adaptive Coupling in Communication Systems
• Mechanisms of Adaptation in Turn-Taking Behavior
• How Adaptive Coupling Facilitates Effective Communication
• Agent-Based Models for Simulating Adaptive Coupling

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Chapter 4: Intersubjectivity and Shared Intentions

• Defining Intersubjectivity in Social Interaction
• The Importance of Shared Intentions in Turn-Taking
• Cognitive and Social Mechanisms Behind Intersubjectivity
• Modelling Intersubjectivity in Computational Simulations

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Chapter 5: Simulation of Turn-Taking Behavior

• Simulation Frameworks for Studying Turn-Taking
• Designing Virtual Agents for Simulating Communication
• The Role of Adaptive Systems in Simulated Turn-Taking
• Case Studies of Turn-Taking Simulation Experiments

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Chapter 6: Agent-Based Models for Turn-Taking

• The Basics of Agent-Based Modelling (ABM) in Communication Studies
• Designing Agents to Simulate Turn-Taking
• Interaction Protocols and Communication Strategies for Agents
• Evaluating Turn-Taking in Simulated Multi-Agent Systems

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Chapter 7: The Role of Feedback in Turn-Taking

• Feedback Mechanisms in Human Communication
• Real-Time Adaptation of Turn-Taking Behavior
• Modelling Feedback Loops in Simulated Turn-Taking Systems
• Impact of Feedback on Intersubjectivity and Communication Efficiency

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Chapter 8: Empirical Studies and Experiments

• Overview of Real-World Experiments on Turn-Taking
• Comparing Simulated and Human Turn-Taking Patterns
• Data Collection from Simulated Turn-Taking Interactions
• Insights from Empirical Research on Adaptive Coupling and Intersubjectivity

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Chapter 9: Applications of Turn-Taking in AI and Robotics

• Implementing Turn-Taking in Human-Robot Interaction
• Adaptive Coupling in Dialogue Systems and Conversational Agents
• Applications in Virtual Assistants and Social Robotics
• Challenges in Real-World Application of Turn-Taking Models

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Chapter 10: Future Directions and Open Problems

• Current Challenges in Modelling Complex Turn-Taking Behaviors
• Advances in AI and Machine Learning for Enhancing Simulated Communication
• The Role of Emotion and Empathy in Turn-Taking Systems
• Future Research Directions in Intersubjectivity and Adaptive Coupling

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