Abstract
This paper describes research on the use of explicitly programmable complex dynamical systems as a high-level parallel programming methodology. We show how problem solving can be seen as two processes interacting at a micro-level, namely selection and combination. These processes originate from the application of simple rules to pairs of elementary solution constituents.
The example discussed here is the emergence of trees. We show how to bias the system towards certain types of solutions. Finally, we discuss the conditions under which local minima problems can be avoided.
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References
Haken, H., (1977), Synergetics, An Introduction, Springer Verlag.
Moyson, F., Manderick, B., (1988), The Collective Behavior Of Ants: An Example of Self-Organisation in Massive Parallelism, VUB AI-MEMO 88-7.
Paredis, J., (1989), The Emergence of Data Structures from Local Interactions, VUB AI-MEMO 89-1 (the long version of this paper).
Steels, L., (1988), Artificial Intelligence & Complex Dynamics, VUB AI-MEMO 88-2.
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© 1991 Springer-Verlag Berlin Heidelberg
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Paredis, J. (1991). The emergence of data structures from local interactions. In: Schwefel, HP., Männer, R. (eds) Parallel Problem Solving from Nature. PPSN 1990. Lecture Notes in Computer Science, vol 496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0029783
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DOI: https://doi.org/10.1007/BFb0029783
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Print ISBN: 978-3-540-54148-6
Online ISBN: 978-3-540-70652-6
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