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Pietro Oliveto's research interests are in bio-inspired computation, randomised search heuristics and combinatorial optimisation. His main expertise is the time complexity analysis of bio-inspired search heuristics such as evolutionary algorithms, genetic algorithms and artificial immune systems.
Such analyses shed light on the behaviour and performance of the heuristics for different classes of problems. By explaining how the expected optimisation time depends on problem and algorithmic characteristics, informed choices may be made concerning which heuristic to choose for a problem at hand and how to set its parameters.
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PROCEEDINGS OF THE 2023 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE COMPANION, GECCO 2023 COMPANIONpp.1271-1300, (2023)
Automated Design of Machine Learning and Search AlgorithmsNatural Computing Seriespp.45-71, (2021)
arXiv (Cornell University) (2021)
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