LNAI 2801 Are There Representations in Embodied Evolved Agents Taking Measures 1st Edition by Hezi Avraham, Gal Chechik, Eytan Ruppin ISBN 9783540200574 354020057X

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ISBN 10: 354020057X
ISBN 13: 9783540200574
Author: Hezi Avraham, Gal Chechik, Eytan Ruppin

The question of conceptual representation has received considerable attention in philosophy, neuroscience and embodied evolved agents. Numerous theories on the interpretation of the term ‘representation’ exist, and many arguments have been made for and against the existence of representations in animate and animat agents. Our work studies this question in evolved artificial embodied agents in a quantitatively rigorous manner, for the first time. We develop two measures, based on information theory, to account for representations. These measures are studied by applying them to evolved agents performing a visual categorization, generalized XOR task. Our results show that having quantitative measures still leaves one with arbitrary “threshold values” decisions which permit wide freedom in determining the existence of representations. However, and more importantly, our results show that information-theoretic measures can still be used efficiently to identify discriminative neural patterns and internal structures that characterize a representation, if the latter is formed.

LNAI 2801 Are There Representations in Embodied Evolved Agents Taking Measures 1st Edition Table of contents:

Chapter 1: Introduction to Embodied Evolved Agents

• What Are Embodied Agents?
• The Role of Embodiment in Cognitive and Developmental Science
• Evolutionary Approaches to Agent Design
• Research Questions and Themes of the Book

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Chapter 2: Theoretical Foundations of Representation

• Defining Representation in Cognitive Science
• The Debate: Do Agents Need Representations to Act?
• Representation in Artificial Intelligence vs. Biological Systems
• The Role of Internal Models in Cognitive Systems

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Chapter 3: Evolution and Embodiment in Agent-Based Systems

• Principles of Evolution in Artificial Life and Cognitive Models
• Embodiment as a Key Factor in the Development of Agents
• The Evolutionary Process of Action Selection and Sensory-Motor Integration
• Cognitive and Embodied Perception in Evolved Agents

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Chapter 4: Measuring Action and Sensory Input in Embodied Agents

• Understanding Sensory and Action Representation in Evolved Agents
• Mechanisms of Sensing and Perception in Embodied Systems
• How Embodied Agents Take Measures of Their Environment
• Case Studies of Sensory-Motor Integration in Robots and Artificial Agents

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Chapter 5: The Role of Learning and Adaptation in Evolved Agents

• Learning in Embodied Systems: From Simple Reflexes to Complex Behaviors
• Evolutionary Algorithms for Adaptation and Learning in Agents
• How Agents Adapt to Their Environment Over Time
• The Role of Representation in Learning and Problem Solving

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Chapter 6: Do Evolved Agents Use Representations?

• Theoretical Models of Representation in Cognitive Systems
• Evidence from Embodied Evolved Agents: Do They Use Internal Models?
• Investigating the Role of Representations in Action and Decision Making
• Comparing Agent-Based Models with Biological Cognition: Insights from Evolutionary Systems

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Chapter 7: Experimental Setup and Methodology

• Designing Experiments to Investigate Representation in Evolved Agents
• Computational Models and Simulation Environments
• Metrics for Measuring Representation and Action Effectiveness
• Tools and Frameworks for Analyzing Embodied Evolved Agents

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Chapter 8: Case Studies of Evolved Agents in Action

• Case Study 1: Sensory-Motor Coordination in Evolved Robots
• Case Study 2: Adaptive Behavior in Evolved Virtual Agents
• Exploring the Role of Internal Representations in Action Selection
• Insights from Real-World and Simulated Evolved Agents

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Chapter 9: Implications for Cognitive Science and Artificial Intelligence

• Theoretical Implications for Understanding Representation in AI
• How Findings Contribute to Our Understanding of Cognitive Systems
• Evolving Agents and Artificial Intelligence: A Path Toward Autonomous Systems
• The Future of Embodied Cognition and Its Application to AI Research

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Chapter 10: Future Directions and Open Problems

• Key Open Questions in the Study of Representation in Embodied Agents
• Challenges in Modeling Complex Evolved Cognitive Systems
• Enhancing Agent Autonomy and Adaptive Behavior Through Representations
• Directions for Future Research in Embodied and Evolved Systems

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