Algorithmic iteration for computational intelligence


Primiero, G. 2017. Algorithmic iteration for computational intelligence. Minds and Machines. 27 (3), pp. 521-543.
TitleAlgorithmic iteration for computational intelligence
AuthorsPrimiero, G.

Machine awareness is a disputed research topic, in some circles considered a crucial step in realising Artificial General Intelligence. Understanding what that is, under which conditions such feature could arise and how it can be controlled is still a matter of speculation. A more concrete object of theoretical analysis is algorithmic iteration for computational intelligence, intended as the theoretical and practical ability of algorithms to design other algorithms for actions aimed at solving well-specified tasks. We know this ability is already shown by current AIs, and understanding its limits is an essential step in qualifying claims about machine awareness and Super-AI. We propose a formal translation of algorithmic iteration in a fragment of modal logic, formulate principles of transparency and faithfulness across human and machine intelligence, and consider the relevance to theoretical research on (Super)-AI as well as the practical import of our results.

Research GroupFoundations of Computing group
PublisherSpringer Verlag
JournalMinds and Machines
Publication dates
Online08 Feb 2017
Print01 Sep 2017
Publication process dates
Deposited10 Feb 2017
Accepted24 Jan 2017
Output statusPublished
Accepted author manuscript
Copyright Statement

The final publication is available at Springer via

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