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Unleashing the Agents: From a Descriptive to an Explanatory Perspective in Agent-Based Modelling

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Advances in Social Simulation

Part of the book series: Springer Proceedings in Complexity ((SPCOM))

Abstract

Agent-based modelling endows the experimenter with high levels of flexibility and, consequently, responsibility. Possibly because of that, developing good models is hard. In this work, we engage in the discussion around improving the analytical value and disciplinary acceptance of agent-based social simulation. To this end, this paper includes the proposal to make the agents themselves observers, as opposed to just participants, of the simulation to introduce explanatory power that cannot be leveraged by on descriptive macro-level analysis alone. This is followed by an argument for the use of institutional concepts for any mechanism that seeks to embed quasi-reflective capabilities in an effort to gain accessible explanatory insights from simulations. To exemplify this idea, we apply it to a cooperation game of moderate complexity and finally discuss application opportunities, challenges and future directions.

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Notes

  1. 1.

    See Kravari and Bassiliades [30] for a comprehensive overview. Abar et al. [1]’s survey provides a refined differentiation of platforms by application domains.

  2. 2.

    Bianchi and Squazzoni [5] collated an insightful overview that illustrates the impact of ABM on sociology.

  3. 3.

    For an overview refer to Balke and Gilbert [3].

  4. 4.

    The importance of considering noise in the physical and social environment has been convincingly argued by Macy and Tsvetkova [34].

  5. 5.

    Equally noteworthy is the rebuttal of Grüne-Yanoff’s argument by Elsenbroich [13].

  6. 6.

    At this stage, it is important to acknowledge the anonymous reviewers who provided valuable feedback for further refinement.

  7. 7.

    Noteworthy examples include Swarm [35], MASON [33], NetLogo [48] and Repast [40].

  8. 8.

    Social learning is operationalised as allowing agents to memorise fellow agents’ institutional statement of the last action. For this operationalisation, the assumption is that all actions are overt. Agents’ memory is bounded; they are able to store feedback for the last 100 experienced or observed interactions.

  9. 9.

    We performed 5 runs for each parameter combination for 2000 rounds. All correlation values have been determined using Spearman’s ρ.

  10. 10.

    For the sake of focus, we will concentrate the discussion on the earlier parameters.

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Author information

Authors and Affiliations

  1. Norwegian University of Science and Technology (NTNU), Gjøvik, Norway

    Christopher K. Frantz

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  1. Christopher K. Frantz
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Correspondence to Christopher K. Frantz .

Editor information

Editors and Affiliations

  1. Department of Computer and Systems Sciences, Stockholm University, Kista, Sweden

    Harko Verhagen

  2. Norwegian College of Fishery Science, UiT The Arctic University of Norway, Tromsø, Norway

    Melania Borit

  3. Linnaeus University Centre for Data Intensive Sciences and Applications, Växjö, Sweden

    Giangiacomo Bravo

  4. Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden

    Nanda Wijermans

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Frantz, C.K. (2020). Unleashing the Agents: From a Descriptive to an Explanatory Perspective in Agent-Based Modelling. In: Verhagen, H., Borit, M., Bravo, G., Wijermans, N. (eds) Advances in Social Simulation. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-34127-5_16

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