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Composition Machines: Programming Self-Organising Software Models for the Emergence of Sequential Program Spaces

arXiv 2108.05402 ↗First posted 11 Aug 2021cs.FL cs.AIcited by 0

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Abstract (arXiv)

We are entering a new era in which software systems are becoming more and more complex and larger. So, the composition of such systems is becoming infeasible by manual means. To address this challenge, self-organising software models represent a promising direction since they allow the (bottom-up) emergence of complex computational structures from simple rules. In this paper, we propose an abstract machine, called the composition machine, which allows the definition and the execution of such models. Unlike typical abstract machines, our proposal does not compute individual programs but enables the emergence of multiple programs at once. We particularly present the machine's semantics and provide examples to demonstrate its operation with well-known rules from the realm of Boolean logic and elementary cellular automata.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 39 references that are in the map. First posted on arXiv 11 Aug 2021.

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3 of 39 references.

References · 3

  1. 2020Learning Behavior Trees with Genetic Programming in Unpredictable Environmentscited by 7
  2. 2013Intrinsic universality and the computational power of self-assemblycited by 1
  3. 2020Self-Organizing Software Models for the Internet of Thingscited by 1

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