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Refinement: a rigorous description of autonomous adaptive agents

J. Augustus Bacigalupi (Institute for Augmenting Minds, San Francisco, California, USA)


ISSN: 0368-492X

Article publication date: 11 November 2013




The purpose of this paper is to develop a theoretical framework to empirically test for cognitive behaviour in autonomous adaptive agents.


This project proposes a theoretical framework, or design parameters, inspired by empirically observed phenomena, cognitive behaviours, and thermodynamics. Success of the framework is measured by its capacity to implement, not just a model of select attributes of cognition, but to implement the foundational physical nature of cognition of which all observed behaviours are based.


A rigorous mathematical framework, employing only information theory and conventional physics, is hypothesized to empirically measure for cognitive behaviours.

Research limitations/implications

Empirical studies will be conducted on synthetic agents using the theoretical framework described herein to demonstrate whether or not cognitive behaviours have been achieved.


This paper proposes an alternative form of information processing inspired by evolved organisms, distinct from Turing equivalent machines, able to augment existing human and digital systems.



Augustus Bacigalupi, J. (2013), "Refinement: a rigorous description of autonomous adaptive agents", Kybernetes, Vol. 42 No. 9/10, pp. 1313-1324.



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Copyright © 2013, Emerald Group Publishing Limited

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