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2016 Volume 31
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RESEARCH ARTICLE   Open Access    

BDI agents in social simulations: a survey

  • 1.

    Grenoble Informatics Laboratory

  • 2.

    Toulouse Institute of Computer Science Research

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  • Abstract: Modelling and simulation have long been dominated by equation-based approaches, until the recent advent of agent-based approaches. To curb the resulting complexity of models, Axelrod promoted the KISS principle: ‘Keep It Simple, Stupid’. But the community is divided and a new principle appeared: KIDS, ‘Keep It Descriptive, Stupid’. Richer models were thus developed for a variety of phenomena, while agent cognition still tends to be modelled with simple reactive particle-like agents. This is not always appropriate, in particular in the social sciences trying to account for the complexity of human behaviour. One solution is to model humans as belief, desire and intention (BDI) agents, an expressive paradigm using concepts from folk psychology, making it easier for modellers and users to understand the simulation. This paper provides a methodological guide to the use of BDI agents in social simulations, and an overview of existing methodologies and tools for using them.
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  • Cite this article

    Carole Adam, Benoit Gaudou. 2016. BDI agents in social simulations: a survey. The Knowledge Engineering Review 31(3)207−238, doi: 10.1017/S0269888916000096
    Carole Adam, Benoit Gaudou. 2016. BDI agents in social simulations: a survey. The Knowledge Engineering Review 31(3)207−238, doi: 10.1017/S0269888916000096
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RESEARCH ARTICLE   Open Access    

BDI agents in social simulations: a survey

  • 1.

    Grenoble Informatics Laboratory

  • 2.

    Toulouse Institute of Computer Science Research

  • Published online: 11 August 2016
The Knowledge Engineering Review  31,  2016, 31(3): 207−238  |  Cite this article

Abstract: Abstract: Modelling and simulation have long been dominated by equation-based approaches, until the recent advent of agent-based approaches. To curb the resulting complexity of models, Axelrod promoted the KISS principle: ‘Keep It Simple, Stupid’. But the community is divided and a new principle appeared: KIDS, ‘Keep It Descriptive, Stupid’. Richer models were thus developed for a variety of phenomena, while agent cognition still tends to be modelled with simple reactive particle-like agents. This is not always appropriate, in particular in the social sciences trying to account for the complexity of human behaviour. One solution is to model humans as belief, desire and intention (BDI) agents, an expressive paradigm using concepts from folk psychology, making it easier for modellers and users to understand the simulation. This paper provides a methodological guide to the use of BDI agents in social simulations, and an overview of existing methodologies and tools for using them.

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    Acknowledgments

    • This work has been partially funded by the ACTEUR (‘Spatial Cognitive Agents for Urban Dynamics and Risk Studies’) research project. The ACTEUR project is funded by the French National Research Agency (ANR) under grant number ANR-14-CE22-0002.

    • Please note that neural networks can also be used to generate proactive behaviour, for instance Murata et al. (2014).

    • Agents can also communicate directly via the environment; low-level problems such as communication noise are out of the scope of this paper.

    • http://www.nyu.edu/ccpr/laser/plancinfo.html.

    • www.matsim.org

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    Cite this article
    Carole Adam, Benoit Gaudou. 2016. BDI agents in social simulations: a survey. The Knowledge Engineering Review 31(3)207−238, doi: 10.1017/S0269888916000096
    Carole Adam, Benoit Gaudou. 2016. BDI agents in social simulations: a survey. The Knowledge Engineering Review 31(3)207−238, doi: 10.1017/S0269888916000096
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