Can we reach Pareto optimal outcomes using bottom-up approaches?
July 03, 2016 Β· Declared Dead Β· π COREDEMA@ECAI
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Authors
Victor Sanchez-Anguix, Reyhan Aydogan, Tim Baarslag, Catholijn M. Jonker
arXiv ID
1607.00695
Category
cs.MA: Multiagent Systems
Cross-listed
cs.AI,
cs.GT
Citations
6
Venue
COREDEMA@ECAI
Last Checked
3 months ago
Abstract
Traditionally, researchers in decision making have focused on attempting to reach Pareto Optimality using horizontal approaches, where optimality is calculated taking into account every participant at the same time. Sometimes, this may prove to be a difficult task (e.g., conflict, mistrust, no information sharing, etc.). In this paper, we explore the possibility of achieving Pareto Optimal outcomes in a group by using a bottom-up approach: discovering Pareto optimal outcomes by interacting in subgroups. We analytically show that Pareto optimal outcomes in a subgroup are also Pareto optimal in a supergroup of those agents in the case of strict, transitive, and complete preferences. Then, we empirically analyze the prospective usability and practicality of bottom-up approaches in a variety of decision making domains.
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