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Self-Replicators Emerge from a Self-Organizing Prebiotic Computer World.

B Greenbaum1, A N Pargellis

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Summary

The Amoeba computer platform demonstrates that even with added complexity like pattern-based addressing and entropy, self-replicating code can emerge. It shows a self-organization phase before replicators appear, challenging previous assumptions.

Keywords:
Evolutioncomplexitydiversityemergenceprebioticself-organization

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Area of Science:

  • Computer Science
  • Artificial Life
  • Evolutionary Computation

Background:

  • The Amoeba system simulates the origin of self-replicating machine code (opcodes) from random sequences.
  • It is inspired by the Tierra system and features a universal opcode set without artificial encapsulation.
  • Previous assumptions suggested added complexity would hinder replicator emergence.

Purpose of the Study:

  • To investigate the emergence of self-replicating sequences in a computational environment with enhanced features.
  • To explore the effects of pattern-based addressing and entropy injection on evolutionary processes.
  • To observe if self-organization precedes the formation of self-replicators.

Main Methods:

  • Utilizing the Amoeba computer platform, which models evolution through point mutations and competition for resources.
  • Implementing pattern-based addressing and entropy injection into the simulation.
  • Quantifying self-organization by analyzing opcode frequencies, sequence size distribution, and mutual information of opcode pairs.

Main Results:

  • Contrary to expectations, Amoeba exhibited a rich emergence of self-organization followed by self-replicators.
  • The opcode basis set showed bias, and short opcode building blocks were propagated.
  • Prebiotic building blocks successfully combined to form self-replicating entities.

Conclusions:

  • The Amoeba system demonstrates that complex environments can foster, rather than inhibit, the emergence of self-replication.
  • Self-organization is a key phase preceding the evolution of functional replicators.
  • Computational evolution models can reveal complex emergent behaviors from simple initial conditions.