Stammdaten

Titel: Emergent social norms and their interaction with other means of behavioral control in complex adaptive agent societies
Beschreibung:
In agent societies, social norms emerge from interactions and sharing of information between members of a society [1]. Social norms play a crucial role in many contexts in which (human) agents interact and make decisions, such as politics or organizations. Topics of emergence and enforcement of such norms have been studied in various fields, e.g. multi-agent systems [2]. The economic literature has studied the interplay between exogenously defined social norms and incentive mechanisms, but has widely failed to properly address the emergence of social norms [3]. We follow this line of research and aim at (better) understanding how social norms that emerge in agent societies interact with other means to control behavior in agent societies.
Based on the NK-framework [4], we set up a complex adaptive system that represents an agent society with multiple interacting entities working on a complex set of interdependent binary decision tasks. Agents operate on pairwise-correlated performance landscapes which together form the task environment of the agent society. Agents interact with their peers in social networks and share information about their past actions, which creates desirable behavioral patterns. We refer to these patterns as emergent social norms and model agents to include them in their decision rules. Along with complying to emergent social norms, agents aim at maximizing their performance-based incentives, and apply the approach of goal programming to balance the two objectives. In the proposed complex adaptive system, social norms are recursive in that they emerge from the agents’ previous actions, but, once formed, can feed back to influence the further decision-making process of agents.
Our results suggest that the emergent social norms tend to have an adverse effect on the system’s performance, unless the agents are operating on highly correlated performance landscapes. If parameterized properly, incentive mechanisms can help to offset potential performance loss: for agent societies facing highly (moderately) complex tasks, incentives based on team (individual) performance tend to lead to higher system-level performance. 
Schlagworte: emergence; social norms goal programming;NK-framework
Typ: Angemeldeter Vortrag
Homepage: -
Veranstaltung: Conference on Complex Systems 2020 (Palma de Mallorca / Online)
Datum: 11.12.2020
Vortragsstatus: stattgefunden (online)

Zuordnung

Organisation Adresse
Fakultät für Wirtschaftswissenschaften
 
Institut für Unternehmensführung
 
Abteilung für Controlling und Strategische Unternehmensführung
Universitätsstrasse 67
9020 Klagenfurt
Österreich
   IFU_CSU@aau.at
https://www.aau.at/csu
zur Organisation
Universitätsstrasse 67
AT - 9020  Klagenfurt
Universität Klagenfurt
 
Digital Age Research Center (D!ARC)
 
Doktoratskolleg Decide
Universitätsstr. 65-67
A-9020 Klagenfurt
Österreich
zur Organisation
Universitätsstr. 65-67
AT - A-9020  Klagenfurt

Kategorisierung

Sachgebiete
  • 502044 - Unternehmensführung
  • 101015 - Operations Research
  • 502052 - Betriebswirtschaftslehre
  • 102009 - Computersimulation
Forschungscluster
  • Selbstorganisierende Systeme
  • Humans in the Digital Age
Vortragsfokus
  • Science to Science (Qualitätsindikator: II)
Klassifikationsraster der zugeordneten Organisationseinheiten:
TeilnehmerInnenkreis
  • Überwiegend international
Publiziert?
  • Nein
Arbeitsgruppen
  • DECIDE (Decision-making in a digital environment)

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