9 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- TH Köln - University of Applied SciencesDE7 papers
- Vrije Universiteit AmsterdamNL2 papers
- Danish Ministry of DefenceDK1 paper
- Hochschule Bonn-Rhein-SiegDE1 paper
- Japan Aerospace Exploration AgencyJP1 paper
- Jožef Stefan InstituteSI1 paper
- Leiden UniversityNL1 paper
- Osaka Prefecture UniversityJP1 paper
- Ostwestfalen-Lippe University of Applied Sciences and ArtsDE1 paper
- Université de LorraineFR1 paper
7 papers
Impact of Energy Efficiency on the Morphology and Behaviour of Evolved Robots
Margarita Rebolledo, Daan Zeeuwe, Thomas Bartz-Beielstein +1
Most evolutionary robotics studies focus on evolving some targeted behavior without taking the energy usage into account. This limits the practical value of such systems because en…
Cognitive Capabilities for the CAAI in Cyber-Physical Production Systems
Jan Strohschein, Andreas Fischbach, Andreas Bunte +3
This paper presents the cognitive module of the cognitive architecture for artificial intelligence (CAAI) in cyber-physical production systems (CPPS). The goal of this architecture…
Continuous Optimization Benchmarks by Simulation
Martin Zaefferer, Frederik Rehbach
Benchmark experiments are required to test, compare, tune, and understand optimization algorithms. Ideally, benchmark problems closely reflect real-world problem behavior. Yet, rea…
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…
Surrogate Models for Enhancing the Efficiency of Neuroevolution in Reinforcement Learning
Jörg Stork, Martin Zaefferer, Thomas Bartz-Beielstein +1
In the last years, reinforcement learning received a lot of attention. One method to solve reinforcement learning tasks is Neuroevolution, where neural networks are optimized by ev…
Prediction of neural network performance by phenotypic modeling
Alexander Hagg, Martin Zaefferer, Jörg Stork +1
Surrogate models are used to reduce the burden of expensive-to-evaluate objective functions in optimization. By creating models which map genomes to objective values, these models…
General Board Game Playing for Education and Research in Generic AI Game Learning
Wolfgang Konen
We present a new general board game (GBG) playing and learning framework. GBG defines the common interfaces for board games, game states and their AI agents. It allows one to run c…