Abstract

In this paper, algorithms for inverse engineering preferences based on observable behavior are developed. The algorithms are based on the most commonly used stability concepts in the graph model for conflict resolution methodology and function by reducing the set of possible preference rankings for each decision-maker (DM). The reduction is based on observable moves and counter-moves made by DMs. This procedure assists stakeholders in optimizing their own decision-making process based on information gathered about their opponents and can also be used to improve the modeling of strategic interactions. A simple case study is used to illustrate the applicability of the algorithms.

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