
TL;DR
This paper explores how hypergraph analysis can reveal complex structures of scenarios, highlighting shared and diverging consequences, beyond traditional methods, to better understand causal relations and possibilities.
Contribution
It introduces a novel approach using hypergraph analysis to examine the structure of scenarios, expanding beyond current practices that rely on crossing macro-features.
Findings
Hypergraph analysis uncovers complex scenario linkages.
Shared and diverging consequences are effectively highlighted.
Application demonstrates practical utility of the approach.
Abstract
Scenarios elicit possibilities that may be ignored otherwise, as well as causal relations between them. Even when too little information is available to assess reliable probabilities, the structure of linkages between evoked alternatives and perceived consequences can be analyzed by highlighting shared consequences of different alternatives or, conversely, diverging consequences of apparently similar alternatives. While according to current practice this structure is analyzed by exploring four possibilities obtained by crossing two macro-features, I illustrate the wider possibilities enabled by hypergraph analysis. An application is discussed.
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Taxonomy
TopicsComplex Systems and Decision Making
