On Alan Turing's anticipation of connectionism

Copeland, B. Jack; Proudfoot, Diane

doi:10.1007/bf00413694

Cited by 61 publications

(38 citation statements)

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“…However, Turing's scheme extended McCulloch and Pitts' work in that he also considered the training of such networks with his B-type architecture. This has led to their also being known as -Turing's connectionism‖ [Copeland & Proudfoot, 1996]. Moreover, as Teuscher [2002] has highlighted, Turing's unorganised machines are (discrete) nonlinear dynamical systems and therefore have the potential to exhibit complex behaviour despite their construction from simple elements.…”

Section: Introductionmentioning

confidence: 99%

On dynamical genetic programming: simple Boolean networks in learning classifier systems

Bull

2009

International Journal of Parallel, Emergent and Distributed Sys

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Abstract. Many representations have been presented to enable the effective evolution of computer programs. Turing was perhaps the first to present a general scheme by which to achieve this end.Significantly, Turing proposed a form of discrete dynamical system and yet dynamical representations remain almost unexplored within conventional genetic programming. This paper presents results from an initial investigation into using simple dynamical genetic programming representations within a Learning Classifier System. It is shown possible to evolve ensembles of dynamical Boolean function networks to solve versions of the well-known multiplexer problem. Both synchronous and asynchronous systems are considered.

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Section: Introductionmentioning

confidence: 99%

On dynamical genetic programming: simple Boolean networks in learning classifier systems

Bull

2009

International Journal of Parallel, Emergent and Distributed Sys

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“…that Turing's earlier "Intelligent Machinery" anticipated connectionism (i.e., computation by neural networks) . So far as we have been able to discover, he was the first person to consider building artificial computing machines out of simple, neuron-like elements connected together into networks in a largely random manner [32,33,90]. However , Turing's res earch into neuron-like computation remained unknown to others subsequently working in t he area, even those in Britain . Turing introduced what he called "unorganised machines," giving as examples networks of neuron-like Boolean element s connected together in a largely random fashion.…”

Section: Turing's Anticipation Of Connectionismmentioning

confidence: 99%

The Computer, Artificial Intelligence, and the Turing Test

Copeland

Proudfoot

2004

Alan Turing: Life and Legacy of a Great Thinker

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Summary. We discuss, first, TUring's role in the development of the computer; second , the early history of Artificial Intelligence (to 1956); and third , TUring's famous imit ation game, now universally known as the TUring t est , which he proposed in cameo form in 1948 and t hen more fully in 1950 and 1952. Various objections have been raised to Turin g's test: we describe some of t he most prominent and explain why, in our view, they fail. Turing and the Computer The Turing MachineIn his first major publication, "On Computable Numbe rs, with an Application to t he Entsc heidungs problem" [91] , TUring introduced his "universal computin g machine" and t he id ea essential t o the modern computer -the concept of cont r olling a comput ing machin e's op erations by means of a program of coded ins tructions stored in the machine's memory. This work had a profou nd influenc e on t he development in t he 1940s of t he electronic st ored-progra m digit al com puter -an influence often neglect ed or deni ed by historians of the computer."The univ ersal com puting machine of 1936~now known simply as t he "universal TUring machine"~is an abstract concept ual model. It consists of a scanner and a limi tless memory-tap e that moves back and forward past t he scanne r. The scanne r reads t he symbols on t he tape and writ es further symbols. The machine has a sm all rep ertoire of basic op erati ons; complexity of operation is achieved by chaining to gether basic op erati ons. The machine is universal in t he sense t hat it can be programmed to carry out any calculati on that could be p erformed by a "human computer" -a clerk who works systemat ically and who has unlimit ed time and an endless supply of paper and pe nc ils.The universal machine has a single, fixed table of instructions built into it. These "hard-wired" ins tructions enable the machine to read and execute symbolically encode d instructions inscrib ed on its t ap e. The data to be worked on are also insc ri be d on the memory-t ap e. By inscribing different programs 1 See, for example, Campb ell-Kelly and Aspray [15]. The nature and scope of TUring's influence is underplayed even in Hodges' biography of Turing [48].C. Teuscher (ed.), Alan Turing: Life and Legacy of a Great Thinker

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“…Likewise, Jack Copeland's extensive work on the history and philosophy of computing has shown how broad and original were Turing's theoretical and philosophical contributions. As well as identifying, editing, and interpreting a large body of neglected primary material by and about Turing (Copeland 2004(Copeland , 2005, Copeland has revivified interest in Turing's work on nonclassical computability (Copeland and Sylvan 1999), argued that Turing anticipated key ideas of connectionism (Copeland and Proudfoot 1996), and corrected prevalent misunderstandings of the Church-Turing thesis (Copeland 1997). Turing's wider views on the idea that the mind is a machine (Copeland 2000a) have been discussed most in relation to the Turing Test for machine intelligence (Copeland 2000b;Proudfoot and Copeland 2009;Oppy and Dowe 2011) and John Searle's Chinese Room argument against machine intelligence (Cam 1990a;Chalmers 1992;Copeland 2002;Tanaka 2004;Coutts 2008).…”

Section: Cognitivism Computation and Contentmentioning

confidence: 99%