Limits to Computability
In the late 1930′s, the UK mathematician Alan Turing established fundamental limits to what we can reasonably expect to know about computations. Turing invented a very simple model of computation called a Turing Machine (TM), which uses a set of rules (quintuplets) to process a sequence of data symbols (tape). Turing explored the seemingly simple question of whether it′s possible to tell if an arbitrary TM will ever stop processing an arbitrary tape, and concluded that it is not possible: the Halting Problem for TMs is undecidable.
TMs have been shown to be equivalent to contemporary computer systems and programming languages, so this result has deep implications for what we can and can′t do with computers. For example, if we can′t tell whether or not an arbitrary program ever terminates then we can′t know in advance how long it will run for or how much memory it will need or how much power it will consume. We also can′t tell whether or not two arbitrary programs actually carry out the same computation. Of course it is possible to solve these problems for particular programs, it just isn′t possible in general.
People still question Turing′s results and try to come up with ways round them. For example, attempts are made to develop new mathematical characterisations of computation (e.g. ″hypercomputation″ or ″superTuring″) that are more powerful than TMs, or to design hardware systems based on novel ideas from physics that can overcome apparent physical limitations to TMs. On the other hand, people also misuse Turing′s results to argue that human beings are necessarily more powerful than computers because they don′t share these limitations, or that there are fundamental limits to particular forms of rule based human activity, such as economic planning.
We are very interested in exploring and challenging such claims. While we are certainly open to new ways of looking at the world, we think that all the evidence shows that Turing′s results say something deep and fundamental about the limits to computability just as the laws of physics place fundamental constraints on how material reality works.
Paul Cockshott, University of Glasgow
Allin Cottrell, Wake-Forest University
Lewis Mackenzie, University of Glasgow
Greg Michaelson, Heriot-Watt University
Our publications include:
P. Cockshott, L. Mackenzie and G. Michaelson, Non-classical computing: feasible versus infeasible, Proceedings of ACM-BCS Visions of Computer Science 2010, University of Edinburgh, April, 2010, to appear PDF
P. Cockshott, L. Mackenzie and G. Michaelson, `Computation and its limits′, Oxford University Press, 2012
Paul Cockshott, `Turing′s Universal Digital Computer′. British Mathematical Colloquium, Kent, April 2012 prezi
Greg Michaelson, `Limits to Computation′, British Mathematical Colloquium, Kent, April 2012 ppt
Greg Michaelson, `A Visit to the Turing Machine′
- CS4Fun, April 2012 here
- Take Tea With Turing, January 2013 - spoken word here
Paul Cockshott and Greg Michaelson, `Tangled Tapes: Infinity, Interaction and Turing Machines′, Turing Centenary Conference: CIE 2012 - How the World Computes, Cambridge, June 2012 PDF of full paper
Paul Cockshott, ′Turing: the irruption of materialism into thought′, OUPBlog , July 2012 - also at Nature: soapboxscience
J. Davidson and G. Michaelson, `Brute force is not ignorance′, Computability in Europe 2013, Milan, June, 2013 PDF
G. Michaelson, ′SKI combinators (really) are Turing complete′, Glasgow, November 2014 - PPTX
`Letter to the editor′, FACS FACTS, Issue 2016-2, December 2016, pp8-13 - PDF
J. Davidson and G. Michaelson, `Expressiveness, meanings and machines′, Computability, 2018 - to appear - PDF
Paul Cockshott, `Turing and Thought′, May 2018 - video
K. Kolozova, P. Cockshott and G. Michaelson, `Defending Materialism. The Uneasy History of the Atom in Science and Philosophy', Bloomsbury, 2024 here
G. Michaelson, Logic & Materialism here - original Chapters 7-10 of `Defending Materialism'