activity
20162025
most citedBenchmarking in Optimization: Best Practice and Open Issues

82 citations · 106 across the 10 of their papers we have counts for

collaborators

12 papers

cs.NE2025

Benchmarking that Matters: Rethinking Benchmarking for Practical Impact

Anna V. Kononova, Niki van Stein, Olaf Mersmann +14

Benchmarking has driven scientific progress in Evolutionary Computation, yet current practices fall short of real-world needs. Widely used synthetic suites such as BBOB and CEC iso…

cs.CY2025★ 3 cited

A Data Literacy Competence Model for Higher Education and Research

Martina M. Echtenbruck, Simone Fühles-Ubach, Boris Naujoks +1

In an increasingly data-driven world, the ability to understand, interpret, and use data - data literacy - is emerging as a critical competence across all academic disciplines. The…

cs.AI2023★ 6 cited

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

Vanessa Volz, Boris Naujoks, Pascal Kerschke +1

The term Procedural Content Generation (PCG) refers to the (semi-)automatic generation of game content by algorithmic means, and its methods are becoming increasingly popular in ga…

cs.LG2022★ 1 cited

Optimally Weighted Ensembles of Regression Models: Exact Weight Optimization and Applications

Patrick Echtenbruck, Martina Echtenbruck, Joost Batenburg +3

Automated model selection is often proposed to users to choose which machine learning model (or method) to apply to a given regression task. In this paper, we show that combining d…

cs.NE2021

Automating Speedrun Routing: Overview and Vision

Matthias Groß, Dietlind Zühlke, Boris Naujoks

Speedrunning in general means to play a video game fast, i.e. using all means at one's disposal to achieve a given goal in the least amount of time possible. To do so, a speedrun m…

cs.NE2020★ 7 cited

Identifying Properties of Real-World Optimisation Problems through a Questionnaire

Koen van der Blom, Timo M. Deist, Vanessa Volz +5

Optimisation algorithms are commonly compared on benchmarks to get insight into performance differences. However, it is not clear how closely benchmarks match the properties of rea…

cs.AI2020

Towards Game-Playing AI Benchmarks via Performance Reporting Standards

Vanessa Volz, Boris Naujoks

While games have been used extensively as milestones to evaluate game-playing AI, there exists no standardised framework for reporting the obtained observations. As a result, it re…

cs.NE2020★ 82 cited

Benchmarking in Optimization: Best Practice and Open Issues

Thomas Bartz-Beielstein, Carola Doerr, Daan van den Berg +14

This survey compiles ideas and recommendations from more than a dozen researchers with different backgrounds and from different institutes around the world. Promoting best practice…

cs.NE2020★ 6 cited

Towards Realistic Optimization Benchmarks: A Questionnaire on the Properties of Real-World Problems

Koen van der Blom, Timo M. Deist, Tea Tušar +5

Benchmarks are a useful tool for empirical performance comparisons. However, one of the main shortcomings of existing benchmarks is that it remains largely unclear how they relate…

cs.NE2020★ 1 cited

Expected Improvement versus Predicted Value in Surrogate-Based Optimization

Frederik Rehbach, Martin Zaefferer, Boris Naujoks +1

Surrogate-based optimization relies on so-called infill criteria (acquisition functions) to decide which point to evaluate next. When Kriging is used as the surrogate model of choi…

cs.NE2016

Surrogate-Assisted Partial Order-based Evolutionary Optimisation

Vanessa Volz, Günter Rudolph, Boris Naujoks

In this paper, we propose a novel approach (SAPEO) to support the survival selection process in multi-objective evolutionary algorithms with surrogate models - it dynamically choos…

cs.HC2016

Demonstrating the Feasibility of Automatic Game Balancing

Vanessa Volz, Günter Rudolph, Boris Naujoks

Game balancing is an important part of the (computer) game design process, in which designers adapt a game prototype so that the resulting gameplay is as entertaining as possible.…