Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2004-09-01
Physics
Condensed Matter
Disordered Systems and Neural Networks
Expanded discussion, including possible applications. Preprint format, now submitted for publication
Scientific paper
We examine the feasibility of predicting and subsequently managing the future evolution of a Complex Adaptive System. Our archetypal system mimics a competitive population of mechanical, biological, informational or human objects. We show that short-term prediction yields corridors along which the system will, with very high probability, evolve. We then show how small amounts of 'population engineering' can be undertaken in order to steer the system away from any undesired regimes which have been predicted. Despite the system's many degrees of freedom and inherent stochasticity, this dynamical 'soft' control over future risk requires only minimal knowledge about the population's composition.
Johnson Neil F.
Smith David M. D.
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