Agent-Based Modeling Of The Role Of Selective Expert Opinion In The Dissemination Of Scientific Ideas Under Uncertainty

dc.contributor.authorWilkins, Emily
dc.date.accessioned2014-04-11T18:17:18Z
dc.date.available2014-04-11T18:17:18Z
dc.date.issued2014-04-11
dc.descriptionDavid Courard-Hauri (Mentor)en_US
dc.description.abstractWe live in a period where large amounts of data are too complex to be easily understood by many interested individuals, who therefore must rely on expert interpretation in order to expand their information about the world. However, in several fields where scientific results are seen to have political implications (for example, climate change, evolution, subjective well-being), oftentimes individuals either seek out or are presented with experts who are preselected for the type of data they are willing to provide. We have developed an agent-based model of interacting individuals seeking to understand a quantitative question in the face of “noisy” data. We use the simulation package NetLogo to study the communication of environmentally relevant scientific information in a heterogeneous society. We investigate the roles of uncertainty, expert interpretation, and intentional information selection in the maintenance of false beliefs even when the agent has a personal incentive to hold beliefs that correspond to exogenous reality The relative importance and power of these influences in the emergence of stable or complex dynamic networks of false belief systems were investigated.en_US
dc.description.sponsorshipDrake University, College of Arts & Sciences, Environmental Science and Policy Programen_US
dc.identifier.urihttp://hdl.handle.net/2092/2047
dc.language.isoen_USen_US
dc.relation.ispartofseriesDUCURS, 2014;58
dc.subjectSelective dissemination of information--Scienceen_US
dc.subjectUncertainty--Influcencesen_US
dc.subjectMultiagent systemsen_US
dc.titleAgent-Based Modeling Of The Role Of Selective Expert Opinion In The Dissemination Of Scientific Ideas Under Uncertaintyen_US
dc.typePresentationen_US
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