LNAI 2801 Evolvability of the Genotype Phenotype Relation in Populations of Self Replicating Digital Organisms in a Tierra Like System 1st Edition by Attila Egri Nagy, Chrystopher Nehaniv ISBN 9783540200574 354020057X

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Product details:
ISBN 10: 354020057X
ISBN 13: 9783540200574
Author: Attila Egri Nagy, Chrystopher Nehaniv

In other Tierra-like systems the genotype is a sequence of instructions and the phenotype is the corresponding executed algorithm. This way the genotype-phenotype mapping is constrained by the structure of a creature’s processor, and this structure was fixed for an evolutionary scenario in previous systems. Our approach here is to put the mapping under evolutionary control. We use a universal processor (analogous to a universal Turing-machine) and put the structural description of the creature’s processor as well as the instruction set of the actual processor into the organism’s genome. The life-cycle of an organism begins with building its actual processor, then the organism can start executing instructions in the rest of its genome with the newly built processor. Since the definitions of the processors and instruction sets are in the genome, they are subject to mutations and heritable variation enabling their evolution. In this work we investigate the evolutionary development of the processor structures. In evolving populations, changes in the components (registers, stacks, queues), variations in instruction-set size and the redefinition of the instructions can be observed during experiments.

LNAI 2801 Evolvability of the Genotype Phenotype Relation in Populations of Self Replicating Digital Organisms in a Tierra Like System 1st Edition Table of contents:

Chapter 1: Introduction to Self-Replicating Systems

• Defining Self-Replicating Digital Organisms
• The Importance of Self-Replication in Evolutionary Theory
• Overview of Digital Evolution and Artificial Life
• Historical Context: The Tierra System and Its Influence
• Key Concepts: Genotype, Phenotype, and Their Interactions

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Chapter 2: Evolutionary Computation and the Tierra-Like System

• The Foundations of Evolutionary Computation
• The Tierra System: A Pioneer in Digital Evolution
• How Tierra Simulates the Evolution of Self-Replicating Organisms
• Adaptation and Evolution in Artificial Life Systems
• The Role of Digital Organisms in Studying Natural Evolution

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Chapter 3: The Genotype-Phenotype Relationship in Evolution

• Understanding the Genotype-Phenotype Mapping
• The Role of Genotypic and Phenotypic Space in Evolutionary Dynamics
• Constraints and Flexibility in Genotype-Phenotype Relationships
• How Evolution Can Be Influenced by the Genotype-Phenotype Structure
• The Impact of Evolution on the Structure of Self-Replicating Systems

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Chapter 4: Measuring Evolvability in Digital Organisms

• Defining Evolvability in Evolutionary Systems
• Methods for Measuring Evolvability in Digital Organisms
• The Impact of Self-Replication on Evolvability
• Experimental Approaches for Assessing Evolvability in Tierra-Like Systems
• Case Studies and Results: Evolvability in Digital Organisms

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Chapter 5: The Role of Population Dynamics in Evolvability

• Population Structure and Its Effects on Evolution
• Interactions Between Individuals in a Population of Digital Organisms
• The Role of Competition, Cooperation, and Mutation in Evolvability
• Simulating Population Dynamics in Tierra-Like Systems
• Effects of Population Size and Diversity on Evolvability

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Chapter 6: Evolutionary Pathways and Adaptation in Digital Organisms

• Exploring Evolutionary Pathways in Self-Replicating Systems
• The Role of Mutation, Crossover, and Selection in Adaptation
• How Digital Organisms Adapt to Environmental Changes
• Pathways to Fitness: How Evolvability Influences Adaptation
• The Limitations and Potential of Evolution in Artificial Systems

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Chapter 7: Empirical Studies and Experimental Results

• Description of Experiments Conducted in Tierra-Like Systems
• Evaluating the Evolvability of Self-Replicating Digital Organisms
• Experimental Results on Genotype-Phenotype Mapping and Evolvability
• Analyzing the Success of Evolutionary Processes in Digital Organisms
• Discussion of Findings: What Makes Evolvability Possible?

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Chapter 8: Theoretical Implications of Evolvability

• Theoretical Insights from Digital Organisms in Evolutionary Computation
• The Relationship Between Self-Replication and Evolvability
• Implications for Understanding Natural Evolutionary Processes
• How Evolvability and Adaptation Relate to Biological Systems
• The Future of Evolvability Research in Digital and Biological Systems

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Chapter 9: Challenges and Limitations of Tierra-Like Systems

• Limitations in Simulating Real-World Evolutionary Processes
• Challenges in Modeling Complex Evolutionary Dynamics
• The Impact of System Constraints on Evolvability
• Balancing Complexity and Simplicity in Evolutionary Models
• Future Directions for Improving Tierra-Like Systems

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Chapter 10: Future Directions in Digital Evolution and Evolvability

• The Future of Digital Evolution and Artificial Life Research
• Exploring New Models for Evolvability in Self-Replicating Systems
• Applications of Evolvability Studies in Computational Biology
• Integrating Evolutionary Computation with Real-World Evolutionary Theory
• Expanding the Scope of Evolvability Research to Other Artificial Life Forms

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Conclusion

• Summary of Key Findings and Contributions
• The Relationship Between Genotype, Phenotype, and Evolvability in Digital Systems
• Final Thoughts on the Role of Evolvability in Artificial Life

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