D-Index & Metrics Best Publications

Mike Preuss

Leiden University
Netherlands

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Computer Science D-index 32 Citations 5,793 227 World Ranking 9095 National Ranking 162

Overview

What is he best known for?

The fields of study Mike Preuss is best known for:

World championship
Championship
Artificial intelligence

Mike Preuss links relevant scientific disciplines such as Set (abstract data type) and Scope (computer science) in the realm of Programming language. His work in Set (abstract data type) is not limited to one particular discipline; it also encompasses Programming language. His work often combines Artificial intelligence and Evolutionary algorithm studies. His multidisciplinary approach integrates Algorithm and Mathematical optimization in his work. His Optimization algorithm research extends to the thematically linked field of Mathematical optimization. He regularly ties together related areas like Heuristics in his Operating system studies. While working on this project, Mike Preuss studies both Machine learning and Algorithm. He undertakes multidisciplinary investigations into Ecology and Competition (biology) in his work. With his scientific publications, his incorporates both Competition (biology) and Ecology.

His most cited work include:

Planning chemical syntheses with deep neural networks and symbolic AI (990 citations)
A Survey of Real-Time Strategy Game AI Research and Competition in StarCraft (179 citations)
Experimental Methods for the Analysis of Optimization Algorithms (96 citations)

What are the main themes of his work throughout his whole career to date

Multi-objective optimization and Pareto principle are all intertwined in Mathematical optimization research. His study brings together the fields of Machine learning and Multi-objective optimization. Mike Preuss integrates Machine learning and Algorithm in his research. With his scientific publications, his incorporates both Algorithm and Mathematical optimization. He links relevant scientific disciplines such as Space (punctuation) and Process (computing) in the realm of Operating system. He undertakes multidisciplinary investigations into Process (computing) and Operating system in his work. Borrowing concepts from Data science, Mike Preuss weaves in ideas under Artificial intelligence. Mike Preuss integrates Data science with Artificial intelligence in his study. His study in Set (abstract data type) extends to Programming language with its themes.

Mike Preuss most often published in these fields:

Artificial intelligence (61.90%)
Mathematical optimization (42.86%)
Algorithm (35.71%)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Planning chemical syntheses with deep neural networks and symbolic AI

Marwin H. S. Segler;Mike Preuss;Mark P. Waller.
Nature (2018)

1018 Citations

A Survey of Real-Time Strategy Game AI Research and Competition in StarCraft

Santiago Ontanon;Gabriel Synnaeve;Alberto Uriarte;Florian Richoux.
IEEE Transactions on Computational Intelligence and AI in Games (2013)

500 Citations

Sequential parameter optimization

T. Bartz-Beielstein;C.W.G. Lasarczyk;M. Preuss.
congress on evolutionary computation (2005)

383 Citations

Exploratory landscape analysis

Olaf Mersmann;Bernd Bischl;Heike Trautmann;Mike Preuss.
genetic and evolutionary computation conference (2011)

273 Citations

Experimental Methods for the Analysis of Optimization Algorithms

Thomas Bartz-Beielstein;Marco Chiarandini;Lus Paquete;Mike Preuss.
Experimental Methods for the Analysis of Optimization Algorithms 1st (2010)

165 Citations

Multiobjective exploration of the StarCraft map space

Julian Togelius;Mike Preuss;Nicola Beume;Simon Wessing.
computational intelligence and games (2010)

156 Citations

Multimodal Optimization by Means of a Topological Species Conservation Algorithm

C Stoean;M Preuss;R Stoean;D Dumitrescu.
IEEE Transactions on Evolutionary Computation (2010)

140 Citations

Towards multiobjective procedural map generation

Julian Togelius;Mike Preuss;Georgios N. Yannakakis.
foundations of digital games (2010)

138 Citations

Procedural Content Generation: Goals, Challenges and Actionable Steps

Julian Togelius;Alex J. Champandard;Pier Luca Lanzi;Michael Mateas.
computational intelligence and games (2013)

133 Citations

Capabilities of EMOA to detect and preserve equivalent pareto subsets

Günter Rudolph;Boris Naujoks;Mike Preuss.
international conference on evolutionary multi criterion optimization (2007)

124 Citations

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Frequent Co-Authors

External Links

Personal Website for Mike Preuss