On the Scalability of Social Order

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

  author =       "Peter Dittrich and Thomas Kron and Wolfgang Banzhaf",
  title =        "On the Scalability of Social Order",
  journal =      "Journal of Artificial Societies and Social
  year =         "2003",
  volume =       "6",
  number =       "1",
  month =        jan,
  keywords =     "genetic algorithms, genetic programming, Artificial
                 Chemistry, Coordination, Double Contingency, Learning,
                 Networks, Self-organization, System Theory",
  ISSN =         "1460-7425",
  URL =          "http://jasss.soc.surrey.ac.uk/6/1/3.html",
  abstract =     "We investigate an algorithmic model based first of all
                 on Luhmann's description of how social order may
                 originate [N. Luhmann, Soziale Systeme, Frankfurt/Main,
                 Suhrkamp, 1984, pp. 148-179]. In a basic 'dyadic'
                 setting, two agents build up expectations during their
                 interaction process. First, we include only two factors
                 into the decision process of an agent, namely, its
                 expectation about the future and its expectation about
                 the other agent's expectation (called
                 'expectation-expectation' by Luhmann). Simulation
                 experiments of the model reveal that 'social' order
                 appears in the dyadic situation for a wide range of
                 parameter settings, in accordance with Luhmann. If we
                 move from the dyadic situation of two agents to a
                 population of many interacting agents, we observe that
                 the order usually disappears. In our simulation
                 experiments, scalable order appears only for very
                 specific cases, namely, if agents generate expectation-
                 expectations based on the activity of other agents and
                 if there is a mechanism of 'information proliferation',
                 in our case created by observation of others. In a
                 final demonstration we show that our model allows the
                 transition from a more actor oriented perspective of
                 social interaction to a systems-level perspective. This
                 is achieved by deriving an 'activity system' from the
                 microscopic interactions of the agents. Activity
                 systems allow to describe situations (states) on a
                 macroscopic level independent from the underlying
                 population of agents. They also allow to draw
                 conclusions on the scalability of social order.",
  notes =        "Is this GP?",

Genetic Programming entries for Peter Dittrich Thomas Kron Wolfgang Banzhaf