Pareto optimality for conditional preference networks with comfort

Abstract

A Conditional Preference Network with Comfort (CPC-net) graphically represents both preference and comfort. Preference and comfort indicate user’s habitual behavior and genuine decisions correspondingly. Given that these two concepts might be conflicting, we find it necessary to introduce Pareto optimality when achieving outcome optimization with respect to a given acyclic CPC-net. In this regard, we propose a backtrack search algorithm, that we call Solve-CPC, to return the Pareto optimal outcomes. The formal properties of the algorithm are presented and discussed.