Field Computation

[picture of field from continuous spatial automaton]

Introduction

A field computer processes fields, that is, spatially continuous arrays of continuous value, or discrete arrays of data that are sufficiently large that they may be treated mathematically as though they are spatially continuous. Field computers can operate in discrete time, like conventional digital computers, or in continuous time like analog computers. (See also the Field Computation Bibliography - under construction.)

Publications (reverse chronological order)

  1. “Transcending Turing Computability” (pdf) Technical Report UT-CS-01-473, November 12, 2001. handouts and slides for a talk are also available.

  2. “Field Computation in Natural and Artificial Intelligence: Extended Version” (pdf), Technical Report CS-99-422, April 14, 1999. Abridged in Information Sciences, Vol. 119 (1999), pp. 73-89. Also available in CogPrint archives.

    A summary (Technical Report CS-98-398, August 21, 1998) is available as compressed postscript and as hypertext. This paper was presented at Neuro-quantum Information Processing session of 3rd International Conference on Computational Intelligence and Neuroscience, Research Triangle Park, NC, October 23-28, 1998.

  3. “Field Computation in Motor Control (pdf)”, by Bruce MacLennan, invited for Self-Organization, Computational Maps and Motor Control, ed. by Pietro G. Morasso and Vittorio Sanguineti, Elsevier, 1997. A version of this paper is available as hypertext (although it contains a few glitches).

  4. “A Computationally Universal Field Computer That is Purely Linear,” [pdf] University of Tennessee, Knoxville, Department of Computer Science Technical Report CS-93-206, September 14, 1993, 28 pp.; by David H. Wolpert and Bruce J. MacLennan. Also Santa Fe Institute Technical Report 93-09-056. This paper proves a particular field computer (a spatial continuum-limit neural net) governed by a purely linear integro-differential equation is computationally universal.

  5. “Field Computation in the Brain” [pdf (308 KB)], by Bruce J. MacLennan, University of Tennessee, Knoxville, Department of Computer Science Technical Report CS-92-174, October 1, 1992, 35 pages. Continuous information representation and processing, field-based theories of sensorimotor intentions and of model-based deduction.

  6. “Research Issues in Flexible Computing: Two Presentations in Japan,” by Bruce J. MacLennan, University of Tennessee, Knoxville, Department of Computer Science Technical Report CS-92-172, September 4, 1992, 17 pages. The text of two presentations made in Japan both of which deal with the Japanese “Real World Computing Project” (informally known as the “Sixth Generation Project”)

  7. “Field Computer Simulator User’s Guide,” by Tomislav Goles, University of Tennessee, Knoxville, Department of Computer Science Technical Report CS-90-124, December 1990, 42 pages. This report describes a simulator for a general purpose field computer. The simulator is implemented as an extension of Common LISP, and provides a set of field transformation operators that we believe will be useful for programming practical applications.

  8. “Continuous Spatial Automata” [pdf] by Bruce J. MacLennan, University of Tennessee, Knoxville, Department of Computer Science Technical Report CS-90-121, November 1990, 9 pages. Definition of continuous spatial automata, in which the cells and their states form a continuum; continuous "Life" as an example. A sequence of example states is also available.

  9. “Field Computation: A Theoretical Framework for Massively Parallel Analog Computation, Parts I–IV,” by Bruce J. MacLennan, University of Tennessee, Knoxville, Department of Computer Science Technical Report CS-90-100, February 1990, 62 pages. This report presents a theoretical framework for understanding and designing massively parallel analog computers. The theory treats computations as continuous transformations of fields which are continuous assemblies of continuous values data.

  10. “Continuous Computation: Taking Massive Parallelism Seriously,” by Bruce J. MacLennan, poster presentation, Los Alamos National Laboratory Center for Nonlinear Studies 9th Annual International Conference, Emergent Computation, Los Alamos NM, May 22-26, 1989. Also University of Tennessee, Knoxville, Department of Computer Science Technical Report CS-89-83, June 1989, 13 pages.

  11. “Outline of a Theory of Massively Parallel Analog Computation,” by Bruce J. MacLennan, poster presentation at IEEE/INNS International Joint Conference on Neural Networks, Washington, D.C., June 18-22, 1989. Abstract in proceedings, Vol II, p. 596. Also University of Tennessee, Knoxville, Department of Computer Science Technical Report CS-89-84, June 1989, 23 pages.

  12. “Field Computation: A Model of Massively Parallel Computation in Electronic, Optical, Molecular and Biological Systems,” by Bruce J. MacLennan, extended abstract in Proceedings of AAAI Spring Symposium, Parallel Models of Intelligence: How Can Slow Components Think So Fast?, Stanford, March 22-24, 1988, pp. 180-183.

  13. “Field Computation and Nonpropositional Knowledge,” by Bruce J. MacLennan, Naval Postgraduate School Technical Report NPS52-87-040, September 1987, 31 pages. [pdf]

  14. “Technology-Independent Design of Neurocomputers: The Universal Field Computer,” by Bruce J. MacLennan, IEEE First Annual International Conference on Neural Networks, June 21-24, 1987. Appears in Proceedings, IEEE First International Conference on Neural Networks, Vol. III, pp. 39-49. [pdf]
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Last updated: 2012-10-19.