Emergent Computation Project

Bruce J. MacLennan, PhD

Department of Electrical Engineering & Computer Science
University of Tennessee, Knoxville

Emergent computation refers to computational processes — in natural or artificial systems — in which information processing and control emerges through the local interaction of large numbers of relatively simple units.  Examples of emergent computation include information processing in the brain, the “swarm intelligence” of social insects and other organisms, embryological morphogenesis (self-organized pattern and structure formation), and molecular computation (such as DNA computation).  The Emergent Computation Project at the University of Tennessee, Knoxville investigates emergent computation in natural and artificial systems and seeks to apply emergent computation in the design of future computer systems, in AI/robotics, and in nanotechnology.  We currently have several projects in progress, described below.

  1. Molecular Combinatory Computation
  2. Artificial Morphogenesis
  3. Embodied Computation
  4. Generalized Computation
  5. Consciousness Studies

Molecular Combinatory Computation

(Supported by NSF)Molecular combinatory computation (MCC) is an approach to molecular computing that makes use of a small set of molecular building blocks and chemical substitution reactions that together have the ability to implement arbitrary computations (i.e., anything computable on a Turing machine).  Therfore MCC provides a means of “programming” the assembly of nanostructures and of controlling their behavior by programmatic means.  We have been investigating MCC by both theoretical analysis and simulation.

Select Publications & Presentations

  1. MacLennan, B.J. “A Formal Model of Universal Algorithmic Assembly and Molecular Computation,” Int’l. Journ. Nanotechnology and Molecular Computation 2, 3 (July–Sept. 2010), pp. 55–67.
  2. MacLennan, B.J. “Molecular Combinatory Computing and its Applications in Nanotechnology.” [old draft: pdf (800KB)]
  3. MacLennan, B.J. “Accomplishments and New Directions for 2004: Progress on Universally Programmable Intelligent Matter — UPIM Report 10,” UT CS Dept. TR UT-CS-04-531, October 2004. [pdf]
  4. “Molecular Combinatory Computing for Nanostructure Synthesis and Control” [postscript (300 KB), pdf (800 KB)]: presented at and appears in proceedings of IEEE Nano 2003, San Francisco, August 12–14, 2003.
  5. MacLennan, B.J. “Universally Programmable Intelligent Matter: A Systematic Approach to Nanotechnology” (presentation at IEEE-Nano, August 28, 2002): Summary for proceedings [postscript, pdf], PowerPoint presentation
For more, please visit the UPIM Project website.

Artificial Morphogenesis

A key unsolved problem in nanotechnology is the assembly of complex 3D hierarchical structures, with control over the structure from the nanoscale up to the macroscopic scale.  Fortunately nature provides an inspiring example of how this can be accomplished: morphogenesis (structure formation) in embryological development, in which cells divide, differentiate, and migrate to self-assemble a complete organism.  We are investigating the computational principles of morphogenesis with the aim of applying artificial morphogenesis to nanotechnology.

Select Publications & Presentations

  1. MacLennan, B.J. “Embodied Computation: Applying the Physics of Computation to Artificial Morphogenesis,” Parallel Processing Letters, 22, 3 (2012). [pdf]
  2. MacLennan, B.J. “Molecular Coordination of Hierarchical Self-Assembly,” invited for Nano Communication Networks Journal, 3, 2 (June 2012), 116–128. [pdf] http://dx.doi.org/10.1016/j.nancom.2012.01.004
  3. MacLennan, B.J. “Embodied Computation: Applying the Physics of Computation to Artificial Morphogenesis,” Proceedings of the Satellite Workshops of UC 2011, TUCS Lecture Notes No. 14, June 2011, pp. 9–20.
  4. MacLennan, B.J. “Models and Mechanisms for Artificial Morphogenesis,” Natural Computing, Springer series, Proceedings in Information and Communications Technology (PICT) 2, ed. by F. Peper, H. Umeo, N. Matsui, and T. Isokawa, Tokyo: Springer, 2010, pp. 23–33. Invited. Preprint [pdf].
  5. MacLennan, B.J. “Artificial Morphogenesis as an Example of Embodied Computation,” International Journal of Unconventional Computing, 7, 1–2 (2011), pp. 3–23.
  6. MacLennan, B.J. “Introduction: Computation and Nanotechnology,” Theoretical and Technological Advancements in Nanotechnology and Molecular Computation: Interdisciplinary Gains, (Bruce MacLennan, ed.), Hershey, NJ: IGI Global, 2011.
  7. MacLennan, B. J. “Morphogenesis as a Model for Nano Communication,” invited for Nano Communication Networks Journal 1 (2010), pp. 199–208. DOI: 10.1016/j.nancom.2010.09.007. [pdf]
  8. MacLennan, B.J. “Models and Mechanisms for Artificial Morphogenesis,” Fourth International Workshop on Natural Computing (IWNC 2009), Himeji Japan, September 23–25, 2009. Slides [pdf (10 MB)] for invited presentation. 
  9. MacLennan, B.J. “Configuration and Reconfiguration of Complex Systems by Artificial Morphogenesis,” Reconfigurable Systems Workshop 2009: Discovery Challenge Thrust, Santa Fe NM, July 20–22, 2009. Sponsored for AFOSR. Slides for invited presentation [pdf (8 MB)]. 
  10. MacLennan, B.J. “A Model of Embodied Computation for Artificial Morphogenesis,” slides [pdf (5 MB)] for Keynote Address, IEEE Alife 2009, Mar. 30 – Apr. 2, 2009, Nashville, TN. A video of this presentation is available (scroll down).  
  11. MacLennan, B.J. “A Model of Embodied Computation Oriented Toward Artificial Morphogenesis,” slides [pdf (1 MB)] for invited talk, The Science and Philosophy of Unconventional Computing (SPUC09), Mar. 23–25, 2009, Cambridge University, Cambridge, UK. They are mostly the same as slides 26–60 of the Alife 2009 Keynote. 
  12. MacLennan, B.J. “Embodied Computing,” invitation-only NSF Workshop on Molecular Communication and Biological Communications Technology, Arlington, VA, Feb. 20–1, 2008. Slides for presentation [pdf (2.1MB)]

Embodied Computation

Post-Moore’s Law computing will require an assimilation between computational processes and their physical realizations, both to achieve greater speeds and densities and to allow computational processes to assemble and control matter at the nanoscale. Therefore, we are investigating embodied computation, which addresses the essential interrelationships of information processing and physical processes in the system and its environment in ways that are parallel to those in the theory of embodied cognition and behavior-based robotics.  There are both challenges and opportunities.  Analysis is more difficult because physical effects must be included, but information processing may be simplified by dispensing with explicit representations and allowing massively parallel physical processes to process information.  Nevertheless, in order to fully exploit embodied computation, we need robust and powerful design methodologies and tools, which are goals of this project.

Select Publications & Presentations

  1. MacLennan, B.J. “Bodies — Both Informed and Transformed: Embodied Computation and Information Processing,” invited submission to Information and Computation, ed. by Gordana Dodig-Crnkovic and Mark Burgin, World Scientific Publishing, in press. Unedited preprint [pdf (1.2 MB)]. 
  2. MacLennan, B.J. “A Model of Embodied Computation for Artificial Morphogenesis,” slides [pdf (5 MB)] for Keynote Address, IEEE Alife 2009, Mar. 30 – Apr. 2, 2009, Nashville, TN. A video of this presentation is available (scroll down). 
  3. MacLennan, B.J. “A Model of Embodied Computation Oriented Toward Artificial Morphogenesis,” slides [pdf (1 MB)] for invited talk, The Science and Philosophy of Unconventional Computing (SPUC09), Mar. 23–25, 2009, Cambridge University, Cambridge, UK. They are mostly the same as slides 26–60 of the Alife 2009 Keynote. 
  4. MacLennan, B.J. “Challenges of Embodied Artificial Intelligence and Robotics,” invited for The ITEA Journal of Test and Evaluation (International Test and Evaluation Association), 29-4 (Dec. 2008 / Jan. 2009).  See also “Test and Evaluation Challenges of Embodied Artificial Intelligence and Robotics,” UT EECS Dept. TR UT-CS-08-628, Aug. 22, 2008 [pdf]. 
  5. MacLennan, B.J. “Aspects of Embodied Computation: Toward a Reunification of the Physical and the Formal,” UT EECS Dept. TR UT-CS-08-610, March 6, 2008; revised Aug. 6, 2008 [pdf].  See also slides [pdf] from a related presentation “Embodiment and Non-Turing Models of Computation” at The 2008 North American Conference on Computing and Philosophy: The Limits of Computation (The International Association for Computing and Philosophy, Bloomington, IN, July 10–12, 2008). 
  6. MacLennan, B.J. “Super-Turing or Non-Turing? Extending the Concept of Computation,” The International Journal of Unconventional Computing 5, 3–4 (2009), Special Issue on Future Trends in Hypercomputation, pp. 369–87. [pdf]
  7. MacLennan, B.J. “Embodied Computing,” invitation-only NSF Workshop on Molecular Communication and Biological Communications Technology, Arlington, VA, Feb. 20–1, 2008. Slides for presentation [pdf (2.1MB)]
  8. MacLennan, B.J. “Self-Organization for Nano-Computation and Nano-Assembly,” Workshop on Emergent Behavior (WEB 07), Oak Ridge National Laboratory, Oak Ridge, TN, March 6–7, 2007.  Slides for presentation [pdf (10.8 MB)]

Generalized Computation

Post-Moore’s Law computing technology will require the exploitation of new physical processes for computational purposes, which will be facilitated by new models of computation. We are developing a model of generalized computation, and a corresponding machine model (the U-machine), which can be applied to massively-parallel nano-computation in bulk materials. Our first design is able to implement quite general transformations on a broad class of topological spaces, which include both analog and digital computation. Neural morphogenesis provides a model for the physical structure of the machine and means by which it may be configured, a process that involves the definition of signal pathways between two-dimensional data areas and the setting of interconnection strengths within them. This approach also provides a very flexible means of reconfiguring of the internal structure of the machine.

Select Publications & Presentations

  1. MacLennan, B.J. “The U-Machine: A Model of Generalized Computation,” International Journal of Unconventional Computing, in press.  See also UT EECS Dept. Technical Report UT-CS-06-587, Dec. 14, 2006.  [pdf (3.4 MB)]
  2. MacLennan, B.J. “Highly Programmable Matter & Generalized Computation: Research in Reconfigurable Analog & Digital Computation in Bulk Materials,” 1st AFRL Reconfigurable Systems Workshop, Air Force Research Laboratory, Albuquerque, NM, Feb. 14–15, 2007.  Slides for presentation [pdf (7.3 MB)]

Consciousness Studies

Consciousness is an essential aspect of intelligence (How intelligently do people act when they are unconscious?), so we have been investigating the emergence of consciousness from the combined activity of masses of neurons.  Consciousness is a prerequisite for implementing intelligent, autonomous robots.

Select Publications

  1. MacLennan, B.J. “Protophenomena and their Physical Correlates,” Journal of Cosmology, 2011, Vol. 14. Invited for special issue on consciousness. 
  2. MacLennan, B.J. “Protophenomena: The Elements of Consciousness and their Relation to the Brain” [preprint pdf]. Invited for Irreducibly Conscious: Selected Papers on Consciousness, ed. by Alexander Batthyány, Avshalom Elitzur & Dimitri Constant, Heidelberg & New York: Universitätsverlag Winter, 2010, ch. X (pp. 189–214).
  3. MacLennan, B.J. “A Protophenomenological Analysis of Synthetic Emotion in Robots,” UT EECS Dept. TR UT-CS-08-623, Aug. 6, 2008 [pdf].  Unedited draft of “Robot React, but Can They Feel?” (Handbook of Research on Synthetic Emotions and Sociable Robotics: New Applications in Affective Computing and Artificial Intelligence, edited by Jordi Vallverdú and David Casacuberta, Hershey, NJ: IGI Global, 2009). 
  4. MacLennan, B.J. “Consciousness: Natural and Artificial” [pdf (440KB)]. Invited for Synthesis Philosophica, Vol. 22 (2008), No. 2, pp. 401–33.
  5. MacLennan, B.J. “Consciousness in Robots: The Hard Problem and Some Less Hard Problems (Extended Version),” UT CS Dept. TR UT-CS-05-553, May 15, 2005.  [pdf (820 KB)]  Extended version of paper [pdf (400K)] presented at 14th IEEE International Workshop on Robot and Human Interactive Communication.
  6. MacLennan, B.J. “The Elements of Consciousness and their Neurodynamical Correlates,” Journal of Consciousness Studies, Vol. 3 (1996), Nos. 5/6, pp. 409–24. Reprinted in Explaining Consciousness: The Hard Problem, Jonathan Shear (Ed.), Cambridge: MIT Press, 1995-7, pp. 249–66. Available as hypertext and in pdf form.
  7. MacLennan, B.J. “ The Investigation of Consciousness Through Phenomenology and Neuroscience.” Invited contribution, Scale in Conscious Experience: Is the Brain Too Important to be Left to Specialists to Study? Joseph King & Karl H.Pribram (Eds.), Mahwah: Lawrence-Erlbaum, 1995, pp. 25–43.

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Last updated: 2013-04-18.