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User:Mike.stannett

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Mike Stannett is a British computer scientist; he is best known for his work in hypercomputation theory, but has also published academic work concerning concurrency theory,[1] software testing,[2] and the theory of X-machines.[3]

Between 1992 and 1997, Stannett worked at both Sheffield University and Cambridge University as an applied economist, publishing joint work with Sean Holly on dynamic time series asymmetries in macroeconomic forecasting.[4] He currently holds a lectureship in Computer Science at Sheffield University, and has served on both the management committee of BCS-FACS, and the Computer Science committee of the London Mathematical Society. He is Principal Investigator on the EPSRC-funded Hypercomputation Research Network,[5] and is associated with the IET/UKCRC Grand Challenge in Computing Research, Journeys in Non-Classical Computation[6][7]

Having been educated at Aylesbury Grammar School, Stannett attended St Peters College (Oxford University), where he obtained a BA in Mathematics in 1983. He obtained his doctorate from Sheffield University in 1986, for work in General Topology concerning the Stone-Čech compactification.[8]

Stannett's research currently focusses mainly on hypercomputation theory, with occasional work on Stream X-Machine Testing (SXMT) strategies for distributed and object-oriented systems. His interest in hypercomputation began in 1986, while researching the theory of X-machines. He introduced the Analog X-Machine (AXM),[9] in which time was represented using the real line R, and argued that the AXM was super-Turing (in contrast, Eilenberg's original X-machine model[10] represents time as a countable sequence of discrete instants, i.e. Eilenberg's model of time is essentially the ring Z of integers). Stannett's original proof of the AXM's hypercomputational nature was ultimately discovered to be incomplete; while fixing the proof, he showed that the AXM is an instance of a more general super-Turing computational model. Called the Timed X-Machine (TXM), this general model leaves the underlying representation of time unfixed; the user is free to define each transition arrow relative to a different model of time. Thus, the X-machine is a TXM in which all transitions are parameterised over Z, and the AXM is a TXM in which all transitions are parameterised over R. Hybrid computers can also be represented as TXM instances, by defining some transitions over Z (or over finite ordinals), and others over R.[11]


References

  1. ^ M. Stannett (1994) Infinite Concurrent Systems - I. The relationship between metric and order convergence. Formal Aspects of Computing, vol. 6, pp. 696-715.
  2. ^ M. Stannett (2006) Simulation Testing of Automata. Formal Aspects of Computing, vol. 18, pp. 31-41.
  3. ^ M. Stannett (2004) X-machines - correctness via testing. FACS FACTS, vol. 2004-02, pp. 32-38.
  4. ^ S. Holly and M. Stannett (1995) Are there asymmetries in UK consumption? A time series analysis. Applied Economics, vol. 27, pp. 767-772.
  5. ^ M. Stannett (2006) HyperNet: Hypercomputation Research Network. Swindon: EPSRC. Online: http://gow.epsrc.ac.uk/ViewGrant.aspx?GrantRef=EP/E064183/1
  6. ^ S. Stepney et al. (2005) Journeys in non-classical computation I: A grand challenge for computing research. Parallel Algorithms Appl. vol. 20, no. (1), pp. 5-19.
  7. ^ M. Stannett (2005) "Industrial Hypercomputation". In S. Stepney (ed.) (2005) The Grand Challenge in Non-Classical Computation International Workshop: 18-19th April 2005. York University, 2005. Online: http://www.cs.york.ac.uk/nature/workshop/papers.htm.
  8. ^ M. Stannett (1986) Internal Topology. PhD Thesis, Department of Pure Mathematics, Sheffield University.
  9. ^ M. Stannett (1990) X-machines and the Halting Problem: Building a super-Turing machine. Formal Aspects of Computing, vol. 2, pp. 331-341.
  10. ^ S. Eilenberg (1974) Automata, Languages and Machines, Vol. A. London: Academic Press.
  11. ^ M. Stannett (2001) Computation over arbitrary temporal models. Technical Report CS-2001-08, Department of Computer Science, Sheffield University, UK.
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