Vis enkel innførsel

dc.contributor.advisorGamback, Bjørnnb_NO
dc.contributor.authorLekvam, Torvaldnb_NO
dc.date.accessioned2014-12-19T13:42:12Z
dc.date.available2014-12-19T13:42:12Z
dc.date.created2014-12-07nb_NO
dc.date.issued2014nb_NO
dc.identifier769301nb_NO
dc.identifierntnudaim:10333nb_NO
dc.identifier.urihttp://hdl.handle.net/11250/253977
dc.description.abstractIt is interesting how we can take a train of thought and transfer this into another person's mind by pushing the air around us. Human language, this complexmedium that distinctly separates humans from animals, has baffled scientists forcenturies. But as it lacks of historical data, researchers wish to benefit fromcomputer science and the field of artificial life to understand the origin oflanguage. This thesis illuminates the potential for using agent-based models toinvestigate the relationship between biology, culture and behavior on anindividual level.This is done in two parts. First, different theories and computational modelsexperimenting with language evolution are presented. This includes a thoroughimplementation of and elaborations on one recent paper, where languageacquisition is illustrated favorable over multiple evolutionary time scales inan agent-based model. In the second part, a more bio-inspired methodology isproposed to make the former model more robust and better suited for extensions.This is demonstrated by letting the agents evolving some social biases, whilethey are conducting a naming game in a social structure. A naming game is anabstraction, often used in the research field, to model the spreading anddiversity of language. Through pair-wise dialogs, the goal of the game is toreach self-organized agreement on naming an arbitrary object in theirenvironment. Given the assumption that communication is beneficial for socialstructure and that social structure is beneficial for reproduction, theexperimental work demonstrates that agents are able to build social structuresthat resembles real life social topologies, although the naming game mighthappen too rapid in respect to the evolving social structure.Hopefully, with support from other disciplines, the presented model is suitedfor further investigation of social, or other functional, traits that caninfluence language evolution.nb_NO
dc.languageengnb_NO
dc.publisherInstitutt for datateknikk og informasjonsvitenskapnb_NO
dc.subjectntnudaim:10333no_NO
dc.subjectMIT informatikkno_NO
dc.subjectKunstig intelligens og læringno_NO
dc.titleCo-evolving Language and Social Structure Using a Genetic Algorithmnb_NO
dc.typeMaster thesisnb_NO
dc.source.pagenumber82nb_NO
dc.contributor.departmentNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for datateknikk og informasjonsvitenskapnb_NO


Tilhørende fil(er)

Thumbnail
Thumbnail
Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel