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Contextual Cognition in Social Simulation

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Abstract

This chapter looks at the modelling of cognition in social simulation with respect to its context-dependency. After making some conceptual clarifications, it briefly reviews existing attempts to include context-like elements into social simulations. It then proposes a principled way, using cognitive context, of integrating machine learning and reasoning processes into a single cognitive model suitable for use in social simulation. This approach is not only particularly suitable for social agents and their coordination but solves several problems at once, including: the feasibility of learning and reasoning, and avoiding over- and under-determination of practical reasoning. Using an example model of an artificial stock market, it shows how context-dependency can make a substantial difference to the outcomes from such models.

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Acknowledgements

The author acknowledges funding from the EPSRC, grant number EP/H02171X/1, as well as discussion with Emma Norling and a great number of people at the Using and Modelling Context conference series.

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Authors and Affiliations

  1. Centre for Policy Modelling, Manchester Metropolitan University, Manchester, UK

    Bruce Edmonds

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  1. Bruce Edmonds
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Correspondence to Bruce Edmonds .

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Editors and Affiliations

  1. University Pierre and Marie Curie (UPMC), Paris, France

    Patrick Brézillon

  2. University of Central Florida, Orlando, Florida, USA

    Avelino J. Gonzalez

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Edmonds, B. (2014). Contextual Cognition in Social Simulation. In: Brézillon, P., Gonzalez, A. (eds) Context in Computing. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-1887-4_18

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  • DOI: https://doi.org/10.1007/978-1-4939-1887-4_18

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