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Found 10 papers, 1 papers with code
Tools for Landscape Analysis of Optimisation Problems in Procedural Content Generation for Games
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.
Optimally Weighted Ensembles of Regression Models: Exact Weight Optimization and Applications
More specifically, in this paper, a heuristic weight optimization, used in a preceding conference paper, is replaced by an exact optimization algorithm using convex quadratic programming.
Automating Speedrun Routing: Overview and Vision
The second part of this paper then refers to the actual speedrun routing optimization problem.
Identifying Properties of Real-World Optimisation Problems through a Questionnaire
Optimisation algorithms are commonly compared on benchmarks to get insight into performance differences.
Benchmarking in Optimization: Best Practice and Open Issues
This survey compiles ideas and recommendations from more than a dozen researchers with different backgrounds and from different institutes around the world.
Towards Game-Playing AI Benchmarks via Performance Reporting Standards
While games have been used extensively as milestones to evaluate game-playing AI, there exists no standardised framework for reporting the obtained observations.
Towards Realistic Optimization Benchmarks: A Questionnaire on the Properties of Real-World Problems
This work aims to identify properties of real-world problems through a questionnaire on real-world single-, multi-, and many-objective optimization problems.
Expected Improvement versus Predicted Value in Surrogate-Based Optimization
Few results from the literature show evidence, that under certain conditions, expected improvement may perform worse than something as simple as the predicted value of the surrogate model.
Surrogate-Assisted Partial Order-based Evolutionary Optimisation
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 chooses individuals to evaluate exactly based on the model uncertainty and the distinctness of the population.
Demonstrating the Feasibility of Automatic Game Balancing
In this paper, the feasibility of automatic balancing using simulation- and deck-based objectives is investigated for the card game top trumps.
