Search Results for author: Tea Tusar

Found 4 papers, 1 papers with code

Tools for Landscape Analysis of Optimisation Problems in Procedural Content Generation for Games

no code implementations • 16 Feb 2023 • Vanessa Volz, Boris Naujoks, Pascal Kerschke, Tea Tusar

This way we aim to provide methods for the comparison of PCG approaches and eventually, increase the quality and practicality of generated content in industry.

Evolutionary Algorithms

Paper
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COCO: The Large Scale Black-Box Optimization Benchmarking (bbob-largescale) Test Suite

1 code implementation • 15 Mar 2019 • Ouassim Elhara, Konstantinos Varelas, Duc Nguyen, Tea Tusar, Dimo Brockhoff, Nikolaus Hansen, Anne Auger

The bbob-largescale test suite, containing 24 single-objective functions in continuous domain, extends the well-known single-objective noiseless bbob test suite, which has been used since 2009 in the BBOB workshop series, to large dimension.

Benchmarking

246

Paper
Code

Using Well-Understood Single-Objective Functions in Multiobjective Black-Box Optimization Test Suites

no code implementations • 1 Apr 2016 • Dimo Brockhoff, Tea Tusar, Anne Auger, Nikolaus Hansen

Several test function suites are being used for numerical benchmarking of multiobjective optimization algorithms.

Benchmarking Multiobjective Optimization

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COCO: The Experimental Procedure

no code implementations • 29 Mar 2016 • Nikolaus Hansen, Tea Tusar, Olaf Mersmann, Anne Auger, Dimo Brockhoff

We present a budget-free experimental setup and procedure for benchmarking numericaloptimization algorithms in a black-box scenario.

Benchmarking

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