2012Frontiers in artificial intelligence and applicationsRequires access

Exploring Metric Sensitivity of Planners for Generation of Pareto Frontiers

Michal Sroka, Long Derek

Open publisher page 7 citations

Abstract

This paper explores how current planners behave when exposed to multiple metrics, examining which of the planners are metric sensitive and which are not. For the metric insensitive planners we propose a new method of simulating metric sensitivity for the purpose of generation of diverse plans close to a pareto frontier. It is shown that metric sensitive planners are good candidates for generating sets of pareto optimal plans.

About this research paper

What this paper is about

This paper explores how current planners behave when exposed to multiple metrics, examining which of the planners are metric sensitive and which are not. For the metric insensitive planners we propose a new method of simulating metric sensitivity for the purpose of generation of diverse plans close to a pareto frontier. It is shown that metric sensitive planners are good candidates for generating sets of pareto optimal plans.

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OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper explores how current planners behave when exposed to multiple metrics, examining which of the planners are metric sensitive and which are not. For the metric insensitive planners we propose a new method of simulating metric sensitivity for the purpose of generation of diverse plans close to a pareto frontier. It is shown that metric sensitive planners are good candidates for generating sets of pareto optimal plans.

Key concepts: Metric (unit), Sensitivity (control systems), Pareto principle, Pareto optimal, Computer science, Mathematical optimization, Operations research, Mathematical economics

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