Title

Beyond Open-Endedness: Quantifying Impressiveness

Abstract

This paper seeks to illuminate and quantify a feature of natural evolution that correlates to our sense of its intuitive greatness: Natural evolution evolves impressive artifacts. Within artificial life, abstractions aiming to capture what makes natural evolution so powerful often focus on the idea of open-endedness, which relates to boundless diversity, complexity, or adaptation. However, creative systems that have passed tests of open-endedness raise the possibility that open-endedness does not always correlate to impressiveness in artificial life simulations. In other words, while natural evolution is both open-ended and demonstrates a drive towards evolving impressive artifacts, it may be a mistake to assume the two properties are always linked. Thus to begin to investigate impressiveness independently in artificial systems, a novel definition is proposed: Impressive artifacts readily exhibit significant design effort. That is, the difficulty of creating them is easy to recognize. Two heuristics, rarity and re-creation effort, are derived from this definition and applied to the products of an open-ended image evolution system. An important result is that that the heuristics intuitively separate different reward schemes and provide evidence for why each evolved picture is or is not impressive. The conclusion is that impressiveness may help to distinguish open-ended systems and their products, and potentially untangles an aspect of natural evolution's mystique that is masked by its co-occurrence with open-endedness. © 2012 Massachusetts Institute of Technology.

Publication Date

1-1-2012

Publication Title

Artificial Life 13: Proceedings of the 13th International Conference on the Simulation and Synthesis of Living Systems, ALIFE 2012

Number of Pages

75-82

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.7551/978-0-262-31050-5-ch011

Socpus ID

84874743926 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84874743926

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