Abstract
This paper introduces “micro-scalability” as a novel design objective for social reasoning architectures operating in open multiagent systems. Micro-scalability is based on the idea that social reasoning algorithms should be devised in a way that allows for social complexity reduction, and that this can be achieved by operationalising principles of interactionist sociology. We first present a formal model of InFFrA agents called m 2 InFFrA that utilises two cornerstones of micro-scalability, the principles of social abstraction and transient social optimality. Then, we exemplify the usefulness of these concepts by presenting experimental results with a novel opponent classification heuristic AdHoc that has been developed using the InFFrA social reasoning architecture. These results prove that micro-scalability deserves further investigation as a useful aspect of socionic research.
This work was supported by DFG (German National Science Foundation) under contracts no. Br609/11-2 and MA759/4-2. The research reported on in this article has continued since the time of writing. Accounts of more recent results can be found in [1,2,3].
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Rovatsos, M., Paetow, K. (2005). On the Organisation of Agent Experience: Scaling Up Social Cognition. In: Fischer, K., Florian, M., Malsch, T. (eds) Socionics. Lecture Notes in Computer Science(), vol 3413. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11594116_9
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DOI: https://doi.org/10.1007/11594116_9
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