Pareto Optimization in Categories
Matilde Marcolli
TL;DR
This paper introduces a categorical framework for Pareto optimization in multi-objective programming and adapts swarm intelligence algorithms to this new formulation.
Contribution
It presents a novel categorical approach to Pareto optimization and modifies swarm algorithms for this context.
Findings
Categorical model of Pareto optimization developed.
Swarm algorithms adapted to categorical resources.
Potential for improved multi-objective resource management.
Abstract
We propose a model of Pareto optimization (multi-objective programming) in the context of a categorical theory of resources. We describe how to adapt multi-objective swarm intelligence algorithms to this categorical formulation.
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Taxonomy
TopicsAI-based Problem Solving and Planning · Complex Systems and Decision Making · Cognitive Science and Mapping