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A Collective Action Simulation Platform

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Multi-Agent-Based Simulation XX (MABS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12025))

Abstract

In this paper, we discuss some types of expectation that contribute to the behaviour of social agents, and investigate the role that these social expectations can play in the resolution of collective action problems. We describe our Collective Action Simulation Platform (CASP), a framework that allows us to integrate the Java-based Repast Simphony platform with a Prolog-based event calculus interpreter. This allows us to run simulations of agents who make reference to social expectations when reasoning about which actions to perform. We demonstrate the use of CASP in modelling a simple scenario involving agents in a collective action problem, showing that agents who are informed by social expectations can be led to cooperative behaviour that would otherwise be considered “non-rational”.

Stephen Cranefield acknowledges funding from the Marsden Fund Council from Government funding, administered by the Royal Society of New Zealand.

The second and third authors contributed to this paper while working at the University of Otago. Hannah Clark-Younger is now at Soul Machines, hannah.clark-younger@soulmachines.com.

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Notes

  1. 1.

    As we are using discrete time simulations, there is always a unique next state—in effect we are using a version of the discrete event calculus  [20].

  2. 2.

    This would apply especially to obligations, which are specialised types of expectations. Currently CASP supports only generic expectations that a programmer can choose to interpret as (e.g.) obligations or commitments within the EC rules provided.

  3. 3.

    https://github.com/maxant/rules.

  4. 4.

    The programmer can also choose to model the effects of physical actions using the EC, or these can be modelled entirely within the Repast agents’ Java code.

  5. 5.

    https://github.com/mvel/mvel.

  6. 6.

    Further extensions to the expectation event calculus reasoner could allow more complex temporal expressions to be used, e.g. a given event should occur once within every occurrence of a recurring time period.

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Authors and Affiliations

  1. Department of Information Science, University of Otago, PO Box 56, Dunedin, New Zealand

    Stephen Cranefield, Hannah Clark-Younger & Geoff Hay

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  1. Stephen Cranefield
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  2. Hannah Clark-Younger
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Correspondence to Stephen Cranefield .

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Editors and Affiliations

  1. ISTC/CNR, Rome, Italy

    Mario Paolucci

  2. Laboratório de Técnicas Inteligentes, Universidade de São Paulo, São Paulo, Brazil

    Jaime Simão Sichman

  3. Institutionen för data- och systemvetenskap, Stockholm University, Kista, Sweden

    Harko Verhagen

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Cranefield, S., Clark-Younger, H., Hay, G. (2020). A Collective Action Simulation Platform. In: Paolucci, M., Sichman, J.S., Verhagen, H. (eds) Multi-Agent-Based Simulation XX. MABS 2019. Lecture Notes in Computer Science(), vol 12025. Springer, Cham. https://doi.org/10.1007/978-3-030-60843-9_6

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  • DOI: https://doi.org/10.1007/978-3-030-60843-9_6

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