On the Organisation of Agent Experience: Scaling Up Social Cognition

Michael Rovatsos, Kai Paetow

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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.
Original languageEnglish
Title of host publicationSocionics
Subtitle of host publicationScalability of Complex Social Systems
EditorsKlaus Fischer, Michael Florian, Thomas Malsch
PublisherSpringer-Verlag
Pages155-175
Number of pages21
ISBN (Electronic)978-3-540-31613-8
ISBN (Print)978-3-540-30707-5
DOIs
Publication statusPublished - 2005

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume3413
ISSN (Print)0302-9743

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