Mitic, P;
(2019)
Adaptive risk consensus models: simulations and applications.
SN Applied Sciences
, 1
, Article 1743. 10.1007/s42452-019-1724-5.
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Abstract
A simulation framework that implements adaptive agent–agent interaction is developed, such that agent behaviour typical of complex adaptive systems is observed. Within this framework, agents monitor the state of the system they inhabit, and adapt their actions so as to optimise a local utility. No central control is present. The context for state is intended to be very general, but is interpreted as risk state, in which optimisation implies a minimisation of risk. Three adaptive interaction modes are proposed. In each, there is a trade-off between simplicity and effectiveness. Additionally a fourth ‘counter-adaptive’ mode is proposed to model situations of a prolonged high risk state. Corresponding ‘real’ examples from recent events are proposed.
| Type: | Article |
|---|---|
| Title: | Adaptive risk consensus models: simulations and applications |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/s42452-019-1724-5 |
| Publisher version: | https://doi.org/10.1007/s42452-019-1724-5 |
| Language: | English |
| Additional information: | This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
| Keywords: | Beta distribution · Consensus · Adaptive · Risk · Convergence · Simulation · Game theory · Dynamical system · Utility function |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10094524 |
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