Complexity 9 (2):19-33 (2003)

This paper presents the architecture and initial feasibility results of a proto-type communication network that utilizes genetic programming to evolve services and protocols as part of network operation. The network evolves responses to environmental conditions in a manner that could not be preprogrammed within legacy network nodes a priori. A priori in this case means before network operation has begun. Genetic material is exchanged, loaded, and run dynamically within an active network. The transfer and execution of code in support of the evolution of network protocols and services would not be possible without the active network environment. Rapid generation of network service code occurs via a genetic programming paradigm. Complexity and Algorithmic Information Theory play a key role in understanding and guiding code evolution within the network
Keywords Kolmogorov complexity  active networks  genetic programming  algorithmic information theory  self‐healing networks  complexity theory
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DOI 10.1002/cplx.20002
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