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Creating New Informational Primitives in Minds and Machines

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Abstract

Creativity involves the generation of useful novelty. Two modes of creating novelty are proposed: via new combinations of pre-existing primitives (combinatoric emergence) and via creation of fundamentally new primitives (creative emergence). The two modes of creativity can be distinguished by whether the changes still fit into an existing framework of possibility, or whether new dimensions in an expanded interpretive framework are needed. Although computers are well suited to generating new combinations, it is argued that computations within a framework cannot produce new primitives for that framework, such that non-computational constructive processes must be utilised to expand the frame. Mechanisms for combinatoric and creative novelty generation are considered in the context of adaptively self-steering and self-constructing goal-seeking percept-action devices. When such systems can adaptively choose their own sensors and effectors, they attain a degree of epistemic autonomy that allows them to construct their own meanings. A view of the brain as a system that creates new neuronal signal primitives that are associated with new semantic and pragmatic meanings is outlined.

Keywords

  • External World
  • Temporal Code
  • Conceptual Primitive
  • Computational Part
  • Neural Assembly

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

  1. 1.

    A Platonist could claim that all sets are open because they can include null sets and sets of sets ad infinitum, but we are only considering here sets whose members are collections of concrete individual elements, much in the same spirit as Goodman (1972).

  2. 2.

    Popular definitions of computation have evolved over the history of modern computing (Boden 2006). For the purposes of assessing the capabilities and limitations of physically-realisable computations, we adopt a very conservative, operationalist definition in which we are justified in calling an observed natural process a computation only in those cases where we can place the observable states of a natural system and its state transitions in a one-to-one correspondence with those of some specified deterministic finite state automaton. This definition has the advantage of defining computation in a manner that is physically-realisable and empirically-verifiable. It results in classifications of computational systems that include both real world digital computers and natural systems, such as the motions of planets, whose observable states can be used for reliable calculation. This finitistic, verificationist conception of computation also avoids conceptual ambiguities associated with Gödel’s Undecidability theorems, whose impotency principles only apply to infinite and potentially-infinite logic systems that are inherently not realisable physically.

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Acknowledgements

I would like to gratefully thank Margaret Boden, Mark d’Inverno, and Jon McCormack and the Leibniz Center for Informatics for organising and sponsoring the Dagstuhl Seminar on Computational Creativity in July 2009 that made this present work possible.

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Cariani, P. (2012). Creating New Informational Primitives in Minds and Machines. In: McCormack, J., d’Inverno, M. (eds) Computers and Creativity. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31727-9_15

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