THE UNIVERSITY OF BIRMINGHAM
School of Computer Science
THE COGNITION AND AFFECT PROJECT

PAPERS ADDED IN AND AFTER 2016

PAPERS 2016-2025 CONTENTS LIST
COGAFF OVERVIEW
COGAFF CONTENTS LIST

NOTE

This file is http://www.cs.bham.ac.uk/research/projects/cogaff/16.html
Maintained by Aaron Sloman -- who does not respond to Facebook requests.
It contains an index to files in the Cognition and Affect Project's Web directory produced or published in the years 2016-2025. Some of the papers published in this period were produced earlier and are included in one of the lists for an earlier period. Some older papers recently digitised may also be included.

Main contents list for the CogAff web site is:
http://www.cs.bham.ac.uk/research/cogaff/0-INDEX.html#contents

A list of PhD and MPhil theses was added in June 2003

This file Renamed: 9 Feb 2020 -- Last Updated: 9 Feb 2020


PAPERS (AND TALKS) IN THE COGNITION AND AFFECT DIRECTORY
Produced or published in or after 2016 (Approximately)


The following Contents Lists (in reverse chronological order) contain links to locations in this file giving further details, including abstracts, and links to the papers themselves.

For a (still incomplete) summary/overview list of key contributions to the CogAff project see The CogAff Project: Papers and presentations on affect, in the Birmingham Cognition and Affect Project started here in 1991, building on earlier work, starting 1969 at Sussex University.

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CONTENTS -- FILES 2020
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CONTENTS -- FILES 2019
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CONTENTS -- FILES 2018 (Latest First)
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CONTENTS -- FILES 2017 (Latest First)
Links to files below. CONTENTS -- FILES 2016(Latest First)

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DETAILS OF DOCUMENTS AND PRESENTATIONS AVAILABLE

2024 Publications
2023 Publications
2023 Publications
2022 Publications
2021 Publications
2020 Publications
Filename: sloman-aidefs-2020.pdf
Title: "A Philosopher-Scientist's View of AI" Journal of Artificial General Intelligence (To appear 2020)
Author: Aaron Sloman
Preprint installed here: 22 Feb 2020
Published version: Not yet available.
DRAFT Invited contribution to a special issue of the Journal of Artificial General Intelligence, with commentaries on Pei Wang's paper "On Defining Artificial Intelligence" JAGI 10(2): 1-37. https://doi.org/10.2478/jagi-2019-0002
Because time was short and space was limited, I presented a view of AI without explicitly comparing it with the contents of the "target" article. I thank the editors for their tolerance. Readers will see differences.
Editors: Dagmar Monett, Colin W. P. Lewis, Kristinn R. Thsrisson
2019 Publications
Filename: kunze-sloman-kij-ai.pdf
Title: "A Philosophically Motivated View on AI and Robotics"
Journal: KI - Kunstliche Intelligenz
Preprint installed here: 1 Nov 2019
Published version: https://doi.org/10.1007/s13218-019-00621-1

Abstract:

Despite AI's enormous practical successes, some researchers focus on its potential as science and philosophy: providing answers to ancient questions about what minds are, how they work, how multiple varieties of minds can be produced by biological evolution, including minds at different stages of evolution, and different stages of development in individual organisms. AI cannot yet replicate or faithfully model most of these, including ancient, but still widely used, mathematical discoveries described by Kant as non-empirical, non-logical and non-contingent. Automated geometric theorem provers start from externally provided logical axioms, whereas for ancient mathematicians the axioms in Euclid's Elements were major discoveries, not arbitrary starting points. Human toddlers and other animals spontaneously make similar but simpler topological and geometrical discoveries, and use them in forming intentions and planning or controlling actions. The ancient mathematical discoveries were not results of statistical/probabilistic learning, because, as noted by Kant, they provide non-empirical knowledge of possibilities, impossibilities and necessary connections. Can gaps between natural and artificial reasoning in topology and geometry be bridged if future AI systems use previously unknown forms of information processing machinery -- perhaps "Super-Turing Multi-Membrane" machinery?
Keywords/phrases:

For more information about the Meta-Morphogenesis project, see
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/meta-morphogenesis.html


2018 Publications

Filename: sloman-ptai17.pdf(PDF)
Title: Huge, Unnoticed, Gaps Between Current AI and Natural Intelligence

Presented at PTAI17 Conference, Univrsity of Leeds, Nov 2017
This is a pre-publication version of the paper to be published by Springer in conference proceedings edited by Vincent Mueller.
Author: Aaron Sloman
Date Installed: 30 Jul 2018

Where published:

To appear in PTAI 2017 Conference proceedings.
Ed. Vincent Mueller, 2018
Abstract:
Despite AI's enormous practical successes, some researchers focus on its potential as science and philosophy: providing answers to ancient questions about what minds are, how they work, how multiple varieties of minds can be produced by biological evolution, including minds at different stages of evolution, and different stages of development in individual organisms. AI cannot yet replicate or faithfully model most of these, including ancient, but still widely used, mathematical discoveries described by Kant as non-empirical, non-logical and non-contingent. Automated geometric theorem provers start from externally provided logical axioms, whereas for ancient mathematicians the axioms in Euclid's Elements were major discoveries, not arbitrary starting points. Human toddlers and other animals spontaneously make similar but simpler topological and geometrical discoveries, and use them in forming intentions and planning or controlling actions. The ancient mathematical discoveries were not results of statistical/probabilistic learning, because, as noted by Kant, they provide non-empirical knowledge of possibilities, impossibilities and necessary connections. Can gaps between natural and artificial reasoning in topology and geometry be bridged if future AI systems use previously unknown forms of information processing machinery -- perhaps "Super-Turing Multi-Membrane" machinery?
Keywords/phrases:
AI as science and philosophy; Can AI model ancient geometers? Can AI model human toddlers? Gaps and limitations of current AI; Super-Turing membrane machines; Replicating mathematical consciousness; Research needed.

For more information about the Meta-Morphogenesis project, see
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/meta-morphogenesis.html


2017 Publications

Filename: sloman_iccm_17.pdf (PDF)
Title: Gaps Between Human and Artificial Mathematics
(Version of 6 page ICCM 2017 paper expanded with full references)


Author: Aaron Sloman
Date installed: 22 Sep 2017

Where published:
Pages 31-36
15th Annual Meeting of the International Conference on Cognitive Modelling
University of Warwick, UK. July 2017

http://mathpsych.org/conferences/2017/
List of abstracts: http://mathpsych.org/conferences/2017/file/MP_ICCM2017_Abstract_Booklet.pdf
Proceedings:

Abstract:

The Turing-inspired Meta-morphogenesis project begun in 2011 was partly motivated by deep gaps in our understanding of mathematical cognition and other aspects of human and non-human intelligence and our inability to model them. The project attempts to identify previously unnoticed evolutionary transitions in biological information processing related to gaps in our current understanding of cognition. Analysis of such transitions may also shed light on gaps in current AI. This is very different from attempts to study human mathematical cognition directly, e.g. via observation, experiment, neural imaging, etc. Fashionable ideas about "embodied cognition", "enactivism", and "situated cognition", focus on shallow products of evolution, ignoring pressures to evolve increasingly disembodied forms of cognition to meet increasingly complex and varied challenges produced by articulated physical forms, multiple sensory capabilities, geographical and temporal spread of important information and other resources, and "other-related meta-cognition" concerning mental states, processes and capabilities of other individuals. Computers are normally thought of as good at mathematics: they perform logical, arithmetical and statistical calculations and manipulate formulas, at enormous speeds, but still lack abilities in humans and other animals to perceive and understand geometrical and topological possibilities and constraints that (a) are required for perception and use of affordances, and (b) play roles in mathematical, and proto-mathematical, discoveries made by ancient mathematicians, human toddlers and other intelligent animals. Neurally inspired, statistics-based (e.g."deep learning") models cannot explain recognition and understanding of mathematical necessity or impossibility. A partial (neo-Kantian) analysis of types of evolved biological information processing capability still missing from our models may inspire new kinds of research helping to fill the gaps. Had Turing lived long enough to develop his ideas on morphogenesis, he might have done this.

Keywords: Archimedes; Euclid; Kant; geometry; topology; vision; evolution; biological information processing; limita- tions of current computational models evolution as a blind mathematician.


Filename: chrisley-sloman-virtual-eucog-2016.pdf (PDF)
Title: Architectural requirements for consciousness

Authors: Ron Chrisley and Aaron Sloman
Date Installed: 21 Sep 2017

Where published:
Pages 31-36
Proceedings of EUCognition 2016 Cognitive Robot Architectures
European Association for Cognitive Systems
Vienna, 8-9 December, 2016
www.eucognition.org
ISSN 1613-0073

Abstract:

Abstract--This paper develops, in sections I-III, the virtual machine architecture approach to explaining certain features of consciousness first proposed in [1] and elaborated in [2], in which particular qualitative aspects of experiences (qualia) are proposed to be particular kinds of properties of components of virtual machine states of a cognitive architecture. Specifically, they are those properties of components of virtual machine states of an agent that make that agent prone to believe the kinds of things that are typically believed to be true of qualia (e.g., that they are ineffable, immediate, intrinsic, and private). Section IV aims to make it intelligible how the requirements identified in sections II and III could be realised in a grounded, sensorimotor, cognitive robotic architecture.

[1] A. Sloman and R. Chrisley, "Virtual machines and consciousness," Journal of Consciousness Studies, vol. 10, pp. 4-5, 2003.
http://www.cs.bham.ac.uk/research/projects/cogaff/03.html#200302

[2] R. Chrisley and A. Sloman, "Functionalism, revisionism, and qualia," APA Newsletter on Philosophy and Computers, vol. 16, pp. 2-13, 2016.
http://www.cs.bham.ac.uk/research/projects/cogaff/16.html#1606


Filename: sloman-aisb17-CandP.pdf (PDF)
Title:
Progress report on the Turing-inspired Meta-Morphogenesis project

Author: Aaron Sloman
Date Installed: 10 Jul 2017

Where published:
Expanded preprint for AISB17 Symposium on Computing and Philosophy,
20th April 2017, Bath University, UK

Abstract:

The Turing-inspired Meta-Morphogenesis project was proposed in the final commentary in Alan Turing - His Work and Impact a collection of papers by and about Turing published (by Elsevier) on the occasion of his centenary. The project was also summarised in a keynote talk at AISB2012, suggesting that an attempt to fill gaps in our knowledge concerning evolution of biological information processing may give clues regarding forms of computation in animal brains that have not yet been re-invented by AI researchers, and this may account for some of the enormous gaps between current AI and animal intelligence, including gaps between ancient mathematicians, such as Euclid and current AI systems. Evolution of information processing capabilities and mechanisms is much harder to study than evolution of physical forms and physical behaviours, e.g. because fossil records can provide only very indirect evidence regarding information processing in ancient organisms. Moreover it is very hard to study all the internal details of information processing in current organisms. Some of the reasons will be familiar to programmers who have struggled to develop debugging aids for very complex multi-component AI virtual machines. The paper presents challenges both for the theory of evolution and for AI researchers aiming to replicate natural intelligence, including mathematical intelligence. This is a partial progress report on attempts to meet the challenges by studying evolution of biological information processing, including evolved construction-kits.


Filename: aisb17-emotions-sloman.html (HTML)
Filename: aisb17-emotions-sloman.pdf (PDF)
Title:
Architectures Underlying Cognition and Affect in Natural and Artificial Systems

Author: Aaron Sloman
Date Installed: 7 Jul 2017

Where published: AISB 2017 Invited talk for Emotions Symposium

Abstract:

This is a summary of some of the ideas in my invited talk for the Symposium on "Computational modelling of emotion: theory and applications" at AISB 2017. A deep understanding of human (or animal) minds requires a broad and deep understanding of the types of information processing functions and information processing mechanisms produced by biological evolution, and how those functions and mechanisms are combined in architectures of increasing sophistication and complexity over evolutionary trajectories leading to new species, and how various kinds of evolved potential are realised by context-sensitive mechanisms during individual development. Some aspects of individual development add context-specific detail to products of the evolutionary history, partly because evolution cannot produce pre-packaged specifications for complete information processing architectures, except for the very simplest organisms. Instead, for more complex organisms, including humans, different architectural layers develop at different times during an individual's life, partly under the influence of the genome and partly under the influence of what the individual has so far experienced, learnt, and developed. This is particularly obvious in language development in humans, but that is a special case of a general biological pattern (identified in joint work with Jackie Chappell, partly inspired by theories of Annette Karmiloff-Smith, among others). This paper complements a paper presented in the Symposium on Computing and Philosophy at AISB 2017, which develops more general ideas about evolution of information processing functions and mechanisms, partly inspired by Turing's work on morphogenesis:
http://www.cs.bham.ac.uk/research/projects/cogaff/sloman-aisb17-CandP.pdf

Filename: incomputable-kits-sloman.pdf (PDF)
Title: Construction Kits for Biological Evolution

Pre-publication version Dec 2016, Published by Springer, 2017
Author: Aaron Sloman
Date Installed: 25 May 2017

Where published:

Invited contribution to: The Incomputable: Journeys Beyond the Turing Barrier
Eds. Mariya Soskova and S Barry Cooper, 2017
(Note: Barry Cooper died in October 2016, before the book went to press.)
http://www.springer.com/gb/book/9783319436678

Abstract:

This is part of the Turing-inspired Meta-Morphogenesis project, which aims to identify transitions in information processing since the earliest proto-organisms, in order to provide new understanding of varieties of biological intelligence, including the mathematical intelligence that produced Euclid's Elements. (Explaining evolution of mathematicians is much harder than explaining evolution of consciousness!) Transitions depend on "construction kits", including the initial "Fundamental Construction Kit" (FCK) based on physics, and Derived Construction Kits (DCKs) produced by evolution, development, learning and culture. Some construction kits (e.g. Lego, Meccano, plasticine, sand) are concrete: using physical components and relationships. Others (e.g. grammars, proof systems and programming languages) are abstract: producing abstract entities, e.g. sentences, proofs, and new abstract construction kits. Mixtures of the two are hybrid kits. Some are meta-construction kits: they are able to create, modify or combine construction kits. Construction kits are generative: they explain sets of possible construction processes and possible products, with mathematical properties and limitations that are mathematical consequences of properties of the kit and its environment. Evolution and development both make new construction kits possible. Study of the FCK and DCKs can lead us to new answers to old questions, e.g. about the nature of mathematics, language, mind, science, and life, exposing deep connections between science and metaphysics. Showing how the FCK makes its derivatives, including all the processes and products of natural selection, possible is a challenge for science and philosophy. This is a long-term research programme with a good chance of being progressive in the sense of Lakatos. Later, this may explain how to overcome serious current limitations of AI (artificial intelligence), robotics, neuroscience and psychology.

For more information about the Meta-Morphogenesis project, see
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/meta-morphogenesis.html

Extract from Editor's introduction to the volume (Mariya I. Soskova)

The final chapter in this book is a special one. Aaron Sloman reports on his "Meta-Morphogenesis project". This project takes the ideas from Turing's original paper and transforms them to a whole new plane of topics: the evolution of biological and human intelligence. The idea for this project was born when Barry Cooper asked Aaron Sloman to contribute to the book "Alan Turing: His Work and Impact" with a chapter related to Turing's work on morphogenesis. Aaron Sloman, whose prior work was most significantly in artificial intelligence, responded to Barry's challenge with this novel idea and has been working on it ever since, motivated by his intuition that this project can lead to answers to fundamental questions: about the nature of mathematics, language, mind, science, life and on how to overcome current limitations of artificial intelligence.
NOTE:
This paper was a snapshot of wor in progress, early in 2016. A few minor improvements were included in the published version (after removal of a host of errors and unwanted "improvements" made by Springer Copy-editors). Meanwhile, work on the theory of evolved construction kits continues, and the most recent update can be found here
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/construction-kits.html

2016 Publications

Filename: chrisley-sloman-PhilCompNL16-1.pdf(PDF)
Title: Functionalism, revisionism, and qualia.

Authors: Chrisley, Ron and Sloman, Aaron
Date Installed: 13 Nov 2017

Where published:
APA Newsletter on Philosophy and Computers, 16 (1). pp. 2-13. ISSN 2155-9708

Abstract:

We discuss revisionism about qualia--the view that tries to navigate between naive qualia realism and reductive eliminativism and discuss the relevance of our approach to AI, explainin in outline how it is possible for them to exist and to play important roles in both scientific explanations and engineering designs.

This extends the discussion in
Sloman, A., and R. Chrisley. "Virtual Machines and Consciousness",
Journal of Consciousness Studies 10 (2003): 113-72.
http://www.cs.bham.ac.uk/research/projects/cogaff/03.html#200302


Presentation (PDF): sloman-pacs-2016.pdf
Presentation (HTML): sloman-pacs-2016.html
Title: Robot Intelligence vs. Biological Intelligence?
A discussion based on Physics, Chemistry, Biology, Mathematics, Mind-Science and Philosophy

Full proceedings of conference PACS2016_Proceedings.pdf(14MB)

Invited talk at PACS 2016 (Seoul, South Korea, 27-8 October 2016):
http://www.kiise.or.kr/pacs/2016/
The International Symposium on Perception, Action, and Cognitive Systems (PACS) is a premier venue for the science and engineering of embodied cognitive systems that sense, act, reason, and learn in real-world environments. The fundamental significance of embodied cognitive systems has long been recognized in science, but its industrial importance realized only recently by new technologies, such as the Internet of things, mixed reality, wearable devices, personal robots, and autonomous cars. The goal of PACS is to bring international researchers from academia and industry together to present recent progresses and discuss new frontiers in interdisciplinary research and convergence technologies for embodied cognitive systems.
Location: AT Center 27, Gangnam-daero, Seocho-gu, Seoul, Korea

Abstract:

Alan Turing died in 1954. The Meta-Morphogenesis project is a conjectured answer to the question: what might Alan Turing have worked on if he had continued several decades after publication of his 1952 paper "The Chemical Basis of Morphogenesis"[Note], instead of dying two years later? The project has many strands, including identifying what needs to be explained -- e.g. how could evolution have produced the brains of mathematicians like Pythagoras, Archimedes and Euclid?; or the brains of human toddlers who seem to make and use topological discoveries before they can talk? Or the brains of intelligent non-humans, like squirrels, weaver birds, elephants and dolphins? How did those ancient human brains make their amazing, deep discoveries over two millennia ago -- long before the development of modern logic or proof-theory? What features of the "fundamental construction kit" (FCK) provided by physics and chemistry made that possible? What sorts of "derived construction kits" (DCKs) were required at various stages of evolution of increasingly complex and varied types of biological information processing? Were some currently unrecognized forms of information processing required that will be needed by future Archimedes-like robots -- e.g. in order to be able to discover that extending Euclidean geometry with the neusis construction allows arbitrary angles to be trisected? A major task of the project is collection and analysis of examples of natural intelligence that current AI cannot match, and current neuroscience cannot explain, to help steer research towards new subgoals. One of my goals is to explain why Immanuel Kant was right about the nature of mathematical discovery in 1781 even if he missed some important details. The presentation will be a revised version of my IJCAI 2016 tutorial. An introduction and some messy notes are here: http://www.cs.bham.ac.uk/research/projects/cogaff/misc/sloman- tut-ijcai-2016.html [Still being revised and extended.]
(Note: Now Turing's most-cited paper)

Invited lecture, Jerusalem 2nd June 2016
What's information? An answer from physics, biology, and philosophy
Aaron Sloman

Presented at The 30th Annual International Workshop on the History and Philosophy of Science Information and information-processing in science: Biology, Physics, and Brain & Cognitive Sciences Research Workshop of the Israel Science Foundation
Monday-Thursday, 30 May - 2 June, 2016
Recording on Youtube
Also available here: here (WEBM, 196MB)
Abstract

The Meta-Morphogenesis (M-M) project was inspired by the question: "What would Turing have worked on if, instead of dying two years after publication of his morphogenesis paper (1952), he had lived several more decades?" My conjectured answer is: he would have tried to explain how a lifeless planet (or universe) could generate all the forms of life, and all the (evolved and still evolving) forms of biological information processing (including mathematical information processing resulting in Euclid's discoveries) that have existed on Earth. This includes the many forms of information-processing required for evolution by natural selection or produced as side-effects, including human uses of language for communication and much older and more wide-spread uses of internal languages for control, perception, learning, planning, desiring, etc. This talk will present some partial results concerning the nature and diversity of biological information and information processing. Most researchers focus on a subset of types of information, and information processing, with bad consequences for science and philosophy.
Online notes:
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/inf-2016-sloman.html

LOVELACE LECTURES Jerusalem Jan 2016
Video Recordings of a two-part lecture in Jerusalem on January 21st 2016.
Evolved construction-kits for building minds
(Evolution's deep learning.)
Speaker: Aaron Sloman
Part of the Ada Lovelace Bicentenary Lectures on Computability, 2015-2016, Jerusalem.

Summary of full programme:
http://ias.huji.ac.il/adalovelacelectures
My local copy of schedule, more easily navigated (no PDF):
http://www.cs.bham.ac.uk/~axs/lovelace-jerusalem.html
Video recordings available on Youtube and here at Bham: ABSTRACT
This will be a highly interactive tutorial introduction to the Turing-inspired Meta-Morphogenesis Project, which brings together a host of problems and ideas about evolution of information processing, how it started on a lifeless planet, how natural selection produced branching layers of construction kits (some physical, some abstract, and some hybrid), and how these made possible increasingly complex and varied morphologies and behaviours based on increasingly complex and varied forms of information processing. Among many topics to be discussed are the unknown evolutionary precursors to human abilities to make mathematical discoveries leading up to Euclid's Elements, and related aspects of human and animal visual abilities. Support for Kant's philosophy of mathematics will be presented, along with criticisms of the visual, mathematical, and linguistic competences of current AI systems. Some possible ways of overcoming those limitations will be considered, with implications for current theories of how brains function.

Expanded abstract available here:
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/lovelace-turing-jan-2016.html
More information on the Meta-Morphogenesis project is available here:
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/m-m-related.html

Some examples of proto-mathematical perceptual capabilities that seem to use mechanisms that are precursors to the discoveries in Euclid's Elements are presented and discussed in
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/impossible.html
Some (Possibly) New Considerations Regarding Impossible Objects
Their significance for mathematical cognition,
and current serious limitations of AI vision systems.

A background paper on evolution of construction kits (Published 2017)
http://www.cs.bham.ac.uk/research/projects/cogaff/17.html#1701
Ongoing work on this topic is here:
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/construction-kits.html


IJCAI 2016 Workshop Paper
Filename:
sloman-bridging-gap-2016.pdf (PDF)
HTML(added 26 May 2021): sloman-bridging-gap-2016.html (HTML)
Title: Natural Vision and Mathematics: Seeing Impossibilities
The paper is about human abilities to make discoveries in geometry and topology, and related abilities in some other intelligent animals -- abilities not yet available to AI reasoning systems. It includes a conjecture about ancient uses of one-to-one correspondences in various human activities, leading to discovery of more powerful and efficent ways of setting up and using such correspondences, that eventually provided a basis for the development of natural number arithmetic.

Author: Aaron Sloman
Date Installed: 7 Jul 2016

Where published:
Second Workshop on: Bridging the Gap between Human and Automated Reasoning, IJCAI 2016
Eds. Ulrich Furbach and Claudia Schon, July, 9, New York, pp.86--101,
http://ratiolog.uni-koblenz.de/bridging2016#Progr

Abstract:

The Turing-inspired Meta-Morphogenesis project investigates forms of biological information processing produced by evolution since the earliest life forms, especially information processing mechanisms that made possible the deep mathematical discoveries of Euclid, Archimedes, and other ancient mathematicians. Such mechanisms must enable perception of possibilities and constraints on possibilities - types of affordance perception not explicitly discussed by Gibson, but suggested by his ideas. Current AI vision and reasoning systems lack such abilities. A future AI project might produce a design for "baby" robots that can "grow up" to become mathematicians able to replicate (and extend) some of the ancient discoveries, e.g. in the way that Archimedes extended Euclidean geometry to make trisection of an arbitrary angle possible. This is relevant to many kinds of intelligent organism or machine perceiving and interacting with structures and processes in the environment. This demonstrates the need to extend Dennett's taxonomy of types of mind to include Euclidean (or Archimedean) minds, and also supports Immanuel Kant's philosophy of mathematics.[*]

Keywords: AI, Kant, Mathematics, Meta-morphogenesis, intuition, Euclid, Geometry,Topology, Kinds-of-minds, Meta-cognition, Meta-meta-cognition, etc.
[*] Extending A.Sloman's DPhil thesis defending Kant's philosophy of mathematics in 1962: https://www.cs.bham.ac.uk/research/projects/cogaff/62-80.html#1962


IJCAI 2016 TUTORIAL
Filename:

     http://www.cs.bham.ac.uk/research/projects/cogaff/misc/sloman-tut-ijcai-2016.html

Title: Notes for tutorial presented at IJCAI2016 New york

Tutorial T24: If Turing had lived longer, how might he have investigated what AI and Philosophy can learn from evolved information processing systems?
Starting with a short session on John McCarthy and Marvin Minsky, two of the founders of AI, recently deceased, both interested in connections between AI and philosophy.
Author: Aaron Sloman
Date Installed: 9 Feb 2020
BACK TO CONTENTS LIST
NOTE
Older files in this directory (pre 2016) are accessible via the main CogAff index
See also the School of Computer Science Web page.

This file is maintained by Aaron Sloman
Email A.Sloman@cs.bham.ac.uk