output
20192021
most citedSurrogate Models for Enhancing the Efficiency of Neuroevolution in Reinforcement Learning

9 citations

6 papers

cs.RO2021

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…

cs.NE20206 cited

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…

cs.NE20206 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.NE20199 cited

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…

cs.NE20198 cited

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…

cs.AI2019

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…