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<article-title>Prediction Horizons in Polyagent Models</article-title>
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<author><a href="mailto:van.parunak@newvectors.net"><name>H. Van Dyke Parunak</name></a></author>
<aff>NewVectors LLC, 3520 Green Court, Suite 250, Ann Arbor, MI, 48105, USA, +1 734 302 5660</aff>

<author><a href="mailto:ted.belding@newvectors.net"><name>Theodore C. Belding</name></a></author>
<aff>NewVectors LLC, 3520 Green Court, Suite 250, Ann Arbor, MI, 48105, USA, +1 734 302 5660</aff>

<author><a href="mailto:sven.brueckner@newvectors.net"><name>Sven Brueckner</name></a></author>
<aff>NewVectors LLC, 3520 Green Court, Suite 250, Ann Arbor, MI, 48105, USA, +1 734 302 5660</aff>

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<title>ABSTRACT</title>
<p>Many agent-based models predict the future. Nonlinear interactions in most non-trivial domains make predictions useless beyond a certain point (the "prediction horizon"), as agent trajectories diverge. We exhibit this behavior in a simple agent-based model, and discuss how a single agent in such a model can estimate the prediction horizon locally and use this estimate to modulate dynamically how far it gazes into the future.</p>
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