Continuous Computation

Introduction

Research in continuous computation (analog computation) focuses on the theoretical similarities and differences between it and discrete (digital) computation, especially with regard to computational theories of intelligence in AI and cognitive science.

Publications (reverse chronological order)

  1. My talk “Transcending Turing Computability,” handouts or slides (both in postscript form).

  2. “Words Lie in Our Way,” by Bruce MacLennan, Minds and Machines, special issue on “What is Computation?” Vol. 4, No. 4 (November 1994), pp. 421-437.

  3. “Image and Symbol: Continuous Computation and the Emergence of the Discrete,” [ps, pdf] by Bruce MacLennan, invited contribution for book, Artificial Intelligence and Neural Networks: Steps Toward Principled Integration, edited by Vasant Honavar and Leonard Uhr, New York, NY: Academic Press, 1994, pp. 207-240. Also University of Tennessee, Knoxville, Department of Computer Science Technical Report CS-93-199, December 18, 1992 (revised August 5, 1993), 33 pages. A proposed theoretical construct (the simulacrum) for connectionist models analogous to the calculus in symbolic models.

  4. “Continuous Symbol Systems: The Logic of Connectionism,” [pdf (370 KB), ps (1.5 MB)] by Bruce MacLennan, Neural Networks for Knowledge Representation and Inference, edited by Daniel S. Levine and Manuel Aparicio IV, Hillsdale, NJ: Lawrence Erlbaum, 1994, pp. 83-120. Also University of Tennessee, Knoxville, Computer Science Department technical report CS-91-145, September 1991, 47 pages. This paper presents a preliminary formulation of continuous symbol systems and indicates how they may aid in understanding the development of connectionist theories.  (N.B.: Some figures are missing from the above electronic versions of this paper.)

  5. “A Universal Field Computer That is Purely Linear,” [ps, pdf] by David H. Wolpert and Bruce J. MacLennan, 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.

  6. “Grounding Analog Computers” [html], by Bruce MacLennan, June 1993. (commentary on S. Harnad, “Grounding Symbols in the Analog World with Neural Nets”), by Bruce MacLennan, Think 2, June 1993, pp. 48-51. Reprinted in Psycoloquy 12 (52), 2001. Also available as postscript and pdf.

  7. “Characteristics of Connectionist Knowledge Representation,” [ps, pdf] by Bruce MacLennan, Information Sciences 70 (1993), pp. 119-143. Also University of Tennessee, Knoxville, Department of Computer Science Technical Report CS-91-147, November 1991, 22 pages. We present a construct, called a simulacrum, which has a similar relation to connectionist knowledge representation as the calculus does to symbolic knowledge representation.

  8. “Continuous Spatial Automata” [pdf] by Bruce 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. “Continuous Computation: Taking Massive Parallelism Seriously,” by Bruce MacLennan, June 1989.
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Last updated: 2007-11-24.