Emerging Artificial Societies Through Learning

Nigel Gilbert (), Matthijs den Besten (), Akos Bontovics (), Bart G.W. Craenen (), Federico Divina (), A.E. Eiben (), Robert Griffioen (), György Hévízi (), Andras Lõrincz (), Ben Paechter (), Stephan Schuster (), Martijn C. Schut (), Christian Tzolov (), Paul Vogt () and Lu Yang ()
Additional contact information
Nigel Gilbert: https://www.surrey.ac.uk/people/nigel-gilbert
Akos Bontovics: http://bontovic.web.elte.hu
A.E. Eiben: http://www.cs.vu.nl/~gusz
Andras Lõrincz: http://people.inf.elte.hu/lorincz
Martijn C. Schut: http://www.cs.vu.nl/~schut
Paul Vogt: http://www.paul-vogt.nl

Journal of Artificial Societies and Social Simulation, 2006, vol. 9, issue 2, 9

Abstract: The NewTies project is implementing a simulation in which societies of agents are expected to de-velop autonomously as a result of individual, population and social learning. These societies are expected to be able to solve environmental challenges by acting collectively. The challenges are in-tended to be analogous to those faced by early, simple, small-scale human societies. This report on work in progress outlines the major features of the system as it is currently conceived within the project, including the design of the agents, the environment, the mechanism for the evolution of language and the peer-to-peer infrastructure on which the simulation runs.

Keywords: Artificial Societies; Evolution of Language; Decision Trees; Peer-To-Peer Networks; Social Learning (search for similar items in EconPapers)
Date: 2006-03-31
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Persistent link: https://EconPapers.repec.org/RePEc:jas:jasssj:2005-53-2

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