Home
Resource
Higher-order analysis of knowledge capacity and learning potential in social animal groups
PDF
PDF format is widely accepted and good for printing.
Plug-in required
PDF-1(4.23 MB)
Citation & Export
View Usage Statistics
Staff View

Citation & Export
Hide

Simple citation

Greening Jr, Bradford. Higher-order analysis of knowledge capacity and learning potential in social animal groups. Retrieved from https://doi.org/doi:10.7282/T3RB7325

Export

Click here for information about Citation Management Tools at Rutgers.

Statistics
Hide

Description

TitleHigher-order analysis of knowledge capacity and learning potential in social animal groups
NameGreening Jr, Bradford (author); Fefferman, Nina H (chair); Smouse, Peter (internal member); Jordan, Rebecca (internal member); Ancel-Meyers, Lauren (outside member); Rutgers University; Graduate School - New Brunswick
Date Created2014
Other Date2014-10 (degree)
SubjectEcology and Evolution, Social behavior in animals, Learning in animals
Extent1 online resource (ix, 131 p. : ill.)
DescriptionThe ability to acquire increased individual knowledge through social dissemination of information is a principal benefit of social living. Information sharing among individuals offers numerous advantages from increased productivity to enhanced problem solving ability. In many cases, pathways formed for information sharing offer a compromise between time spent communicating information among participating individuals and the amount of knowledge amassed by each individual. Network models have yielded many insights into the nature of information sharing via pairwise interactions. However, for many social populations, information sharing does not occur strictly in pairs, but also in groups of three or more. Abstracting these scenarios using network models (or strictly pairwise interactions) may miss fundamental aspects driving the social dissemination of information. Here, I define and utilize a modeling framework based on simplicial sets, a concept from algebraic topology, which allows encapsulation of group interactions of arbitrary size, as well as several other features of higher-order interactions. I first present the concepts needed to implement a simplicial set model, detail advantages of the model in comparison to network models, and provide necessary mathematical definitions in an accessible manner (Chapter 1). I then use simplicial set models to investigate the effects of higher-order communication structure on the ability of a social population to build a global knowledge set (Chapter 2). I subsequently examine how placement of knowledgeable individuals within these higher-order structures affects global knowledge-building ability (Chapter 3). The results of these studies show that simplicial set models capture conceptually different social dynamics than are possible using network models. This model system allows us to investigate how information accumulates via interactions within and between sub-groups, offering insight into complex aspects of higher-order communication systems. The fundamental change in modeling strategy we offer here allows us to move from portraying knowledge as tokens passed from signaler to receiver, to portraying knowledge as building blocks from which novel ideas can emerge. Additionally, this dissertation lays the groundwork for future studies of higher-order social learning and consensus decision-making in social populations using simplicial set models that will both complement and enhance our existing knowledge of social information dissemination.
NotePh.D.
NoteIncludes bibliographical references
Noteby Bradford Greening, Jr.
Genretheses, ETD doctoral
Persistent URLhttps://doi.org/doi:10.7282/T3RB7325
Languageeng
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
Version 8.5.5
Rutgers University Libraries - Copyright ©2024