• Corpus ID: 17501796

Exploring the Concept of Open-Ended Evolution

@inproceedings{Taylor2012ExploringTC,
  title={Exploring the Concept of Open-Ended Evolution},
  author={Tim Taylor},
  year={2012}
}
Extended Abstract The termopen-ended evolution (“OEE”) is used by the ALife community to refer to the kind of long-term evolutionary dynamics observed in the biosphere. It is generally taken to refer to evolutionary systems which display a continual pro duction of adaptively significant innovations. Furthermor e, some authors use the term to imply a sustained increase in complexity and/or diversity of some components of the evolving system; a system capable of open-ended evolution could… 

Necessary Conditions for Open-Ended Evolution

This dissertation describes the first scientific endeavor to systematically test an OEE framework in an alife world and thereby make progress towards solving an open question not just for evolutionary computation and artificial life, but for science in general.

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A brief contribution to Artificial Life journal special issue on open-ended evolution presents a simple evolving computational system that, it is claimed, satisfies all proposed requirements for OEE and presents a "high-level conceptual framework" to help orient the discussion and implementation ofopen-endedness in evolutionary systems.

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This work describes a framework that uses a meta-theory that integrates long-standing foundational theories of systemic change and a two-part machine-intelligent computational modeling, specifically, using network analysis and machine learning models, to characterize resilience.

Observation of Unbounded Novelty in Evolutionary Algorithms is Unknowable

Using standard algorithmic information theory and Chaitin's Incompleteness Theorem, it is proved no algorithm can detect unlimited novelty and observation of unbounded novelty in computer evolutionary programs is nonalgorithmic and, in this sense, unknowable.

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The main contribution is to articulate why open-endedness deserves a place alongside artificial intelligence as one of the great computational challenges, and opportunities, of the authors' time.

Requirements for Open-Ended Evolution in Natural and Artificial Systems

It is argued that these ideas can be seen as aspects of five fundamental requirements for open-ended evolution: robustly reproductive individuals, a medium allowing the possible existence of a practically unlimited diversity of individuals and interactions, individuals capable of producing more complex offspring, mutational pathways to other viable individuals, and drive for continued evolution.

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