The Effects of Generalized Reciprocal Exchange on the Resilience of Social Networks: An Example from the Prehispanic Mesa Verde Region
dc.contributor.author | Reynolds, Robert G. | en_US |
dc.contributor.author | Kohler, Timothy A. | en_US |
dc.contributor.author | Kobti, Ziad | en_US |
dc.date.accessioned | 2006-09-11T15:13:00Z | |
dc.date.available | 2006-09-11T15:13:00Z | |
dc.date.issued | 2003-10 | en_US |
dc.identifier.citation | Reynolds, Robert G.; Kohler, Timothy A.; Kobti, Ziad; (2003). "The Effects of Generalized Reciprocal Exchange on the Resilience of Social Networks: An Example from the Prehispanic Mesa Verde Region." Computational & Mathematical Organization Theory 9(3): 227-254. <http://hdl.handle.net/2027.42/44742> | en_US |
dc.identifier.issn | 1381-298X | en_US |
dc.identifier.issn | 1572-9346 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/44742 | |
dc.description.abstract | The initial version of the model used in this study, Village 1.0, was implemented by Tim Kohler and a team of developers mostly from Washington State University. The original model addressed environmental constraints only and did not attempt to model social interaction. In a recent paper we employed Cultural Algorithms as a framework in which to add selected social considerations. In this paper we extend our previous model by adding the ability of agents to perform symmetrically initiated or asymmetrically initiated generalized reciprocal exchange. We have developed a state model for agents' knowledge and, given agents' different responses based on this knowledge. Experiments have shown that the network structure of the systems without reciprocity was the simplest but least resilient. As we allowed agents more opportunities to exchange resources we produced more complex network structures, larger populations, and more resilient systems. Furthermore, allowing the agents to buffer their requests by using a finite state model improved the relative resilience of these larger systems. Introducing reciprocity that can be triggered by both requestors and donors produced the largest number of successful donations. This represents the synergy produced by using the information from two complementary situations within the network. Thus, the network has more information with which it can work and tended to be more resilient than otherwise. | en_US |
dc.format.extent | 1132822 bytes | |
dc.format.extent | 3115 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Kluwer Academic Publishers; Springer Science+Business Media | en_US |
dc.subject.other | Economics / Management Science | en_US |
dc.subject.other | Artificial Intelligence (Incl. Robotics) | en_US |
dc.subject.other | Management | en_US |
dc.subject.other | Operation Research/Decision Theory | en_US |
dc.subject.other | Methodology of the Social Sciences | en_US |
dc.subject.other | Sociology | en_US |
dc.subject.other | Cultural Algorithm | en_US |
dc.subject.other | Multi-agent | en_US |
dc.subject.other | Network Resilience | en_US |
dc.subject.other | Reciprocity | en_US |
dc.subject.other | Small World Networks | en_US |
dc.subject.other | Archaeology | en_US |
dc.subject.other | U.S. Southwest | en_US |
dc.title | The Effects of Generalized Reciprocal Exchange on the Resilience of Social Networks: An Example from the Prehispanic Mesa Verde Region | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Industrial and Operations Engineering | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Computer Science, Wayne State University, Detroit, MI, 48202, USA; Adjunct Research Associate, Museum of Anthropology, University of Michigan, Ann Arbor, Michigan, 48104, USA | en_US |
dc.contributor.affiliationother | Department of Anthropology, Washington State University, Pullman, WA, 99164-4910, USA | en_US |
dc.contributor.affiliationother | School of Computer Science, University of Windsor, Windsor, ON, Canada, N9B-3P4 | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/44742/1/10588_2004_Article_5270975.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1023/B:CMOT.0000026583.03782.60 | en_US |
dc.identifier.source | Computational & Mathematical Organization Theory | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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