Wild Architecture: Explaining Cognition via Self-Sustaining Systems

Wild Architecture: Explaining Cognition via Self-Sustaining Systems

Vincent T. Cialdella (Illinois State University, USA), Emilio J. C. Lobato (Illinois State University, USA) and J. Scott Jordan (Illinois State University, USA)
Copyright: © 2017 |Pages: 22
DOI: 10.4018/978-1-5225-1947-8.ch003
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Abstract

In this chapter, the authors focus on cognitive architectures that are developed with the intent to explain human cognition. The authors first describe the mission of cybernetics and early cognitive architectures and recount the popular criticism that these perspectives fail to provide genuine explanations of cognition. Moving forward, the authors propose that there are three pervasive problems that modern cognitive architectures must address: the problem of consciousness, the problem of embodiment, and the problem of representation. Wild Systems Theory (Jordan, 2013) conceptualizes biological cognition as a feature of self-sustaining embodied context that manifests itself at multiple, nested, time-scales. In this manner, Wild Systems Theory is presented as a particularly useful framework for coherently addressing the problems of consciousness, embodiment, and representation.
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Introduction

For some time now, one of the leading assumptions in the development of cognitive architectures has been Marr’s (1982) tri-level theory of explanation; the idea that the proper approach in developing a cognitive architecture (and thus explaining cognition) is to

  • 1.

    Determine the computations necessary to completing a cognitive task (e.g., sorting a list of numbers from lowest to highest),

  • 2.

    Generate a representation of the inputs, outputs, and algorithms an information-processing system would need to complete the task, and

  • 3.

    Actually build (i.e., implement) a system capable of executing the algorithms.

The purpose of the present paper is to examine issues that have proven challenging to Marr’s implementation approach to explaining cognition. Three particular challenges are the issues of consciousness, embodiment, and representation. After examining these challenges, we will present an approach to describing cognitive architectures (Wild Systems Theory—WST, Jordan, 20213) that addresses each challenge, while simultaneously shifting the focus of modeling from looking to biology for inspiration, to looking at a more fundamental property that biological systems share with many other types of systems, including chemical, psychological, and cultural—specifically, the ability of certain far from equilibrium systems to generate catalysts that feedback into and sustain the processes that produced them; what Kauffman (1995) refers to as ‘autocatalytic’ systems, and what Jordan (2013) refers to as self-sustaining, or wild systems.

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