Artificial Life and Synthetic Ethology


Artificial life has been defined as “a field of study devoted to understanding life by attempting to abstract the fundamental dynamical principles underlying biological phenomena and recreating these dynamics in other physical media - such as computers - making them accessible to new kinds of experimental manipulation and testing” (Chris Langton; for more, see Artificial Life ONLINE from Santa Fe).

Synthetic ethology is an approach to the study of animal behavior in which simple, synthetic organisms are allowed to behave and evolve in a synthetic world. Because both the organisms and their worlds are synthetic, they can be constructed for specific purposes, particularly for testing specific hypotheses.

Publications (reverse chronological order)

  1. “Synthetic Ethology: A New Tool for Investigating Animal Cognition,” in Marc Bekoff, Colin Allen, and Gordon M. Burghardt (Eds.), The Cognitive Animal: Empirical and Theoretical Perspectives on Animal Cognition (MIT Press, 2002), ch. 20 (pp. 151–156). Expanded version: Technical Report UT-CS-01-462 [postscript, pdf]

  2. “The Emergence of Communication through Synthetic Evolution” [postscript, compressed postscript, pdf], Technical Report UT-CS-99-431, October 20, 1999. Advances in Evolutionary Synthesis of Neural Systems, edited by Vasant Honavar, Mukesh Patel, and Karthik Balakrishnan (MIT Press, 2001), pp. 65–90.

  3. “Preliminary Investigation of Random SKI-Combinator Trees” [compressed postscript], Technical Report CS-97-370, October 20, 1997.

  4. “The Greek Miracle: An Artificial Life Simulation of the Effects of Literacy on the Dynamics of Communication” [compressed postscript], by Andrew Douglas Digh, MS thesis, December 1994. A condensed version (32 pp.) is also avialable. This thesis reports a study of complex systems phenomena motivated by the apparent “phase transition” that took place in ancient Greece when the alphabet was introduced. In particular, the complexity of behavior (Wolfram’s classes I, II, etc.) is related to a parameter analogous to Langton's lambda. Instead of a simple cellular automaton, the topology is given by separate random networks for oral and literate communication.

  5. “Evolution of Two Symbol Signals by Simulated Organisms” [postscript], by Joseph J. Crumpton, MS thesis, December 1994. This thesis reports experiments on the factors promoting or inhibiting the evolution of simulated organisms using strings of length 2 for communication. (The simulation program is also available.)

  6. “Synthetic Ethology and the Evolution of Cooperative Communication” [postscript, compressed postscript, pdf], by Bruce J. MacLennan and Gordon M. Burghardt. Adaptive Behavior, Vol. 2, No. 2, Fall 1993, pp. 161–187. There are eight figures (not included in the above files) in fig 1, fig 2, fig 3, fig 4, fig 5, fig 6, fig 7, fig 8. [If you have trouble diplaying or printing these file, send me mail for a reprint.

  7. “Synthetic Ethology: An Approach to the Study of Communication” [postscript, compressed postscript, pdf], by Bruce MacLennan. Artificial Life II: The Second Workshop on the Synthesis and Simulation of Living Systems, Santa Fe Institute Studies in the Sciences of Complexity, proceedings Vol. X, edited by Christopher G. Langton, Charles Taylor, J. Doyne Farmer, and Steen Rasmussen. Redwood City, CA: Addison-Wesley, 1992, pp. 631–658. Also University of Tennessee, Knoxville, Department of Computer Science Technical Report CS-90-104 [compressed postscript], May 1990, 28 pages.

  8. “Evolution of Communication in a Population of Simple Machines'” (without appendices) [compressed postscript, pdf], Bruce MacLennan. The appendices are available as separate text files: App. 1: instructions for running the simulation program, and App. 2: the simulation program in LISP. University of Tennessee, Knoxville, Department of Computer Science Technical Report CS-90-99, January 1990, 49 pages.

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Last updated: 2013-09-22.