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This is an abstract for a talk to be given at the Fifth Foresight Conference on Molecular Nanotechnology. The full paper is available at http://www.cs.rutgers.edu/~josh/chsmith.html
Molecular nanotechnology will be physically capable of producing objects whose complexity exceeds that of any currently designed artifact by several orders of magnitude. Designs which make more than non-trivial use of this capability are beyond the capabilities of human designers, even using current CAD methods. Thus automatic design, or at least an improvement in automation over existing practice, will be a crucial component of molecular manufacturing.
Central problems in automatic design include the allocation of scarce
resources in the design (e.g. power and materials budgets), managing tradeoffs
between conflicting design goals, and control of the overall design process
itself and the simulations that it entails. The present effort is an investigation
of a mixed-paradigm control model, drawing from evolution (the "genetic
algorithm") and economics ("agoric algorithms"). We show
that this model is a promising formulation for the general control and
integration task. We present experimental results in which it performs
certain desirable control tasks, including rational allocation of effort
in stochastic methods, coordinating local expertise into an overall structure
using the price mechanism, and driving the overall process towards global
J. Storrs Hall, Deptartment of Comp. Science, Rutgers University, New Brunswick NJ 08903, ph: 908-445-3896, fax: 908-445-0537, email: firstname.lastname@example.org
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