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.
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.
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Planning chemical syntheses with deep neural networks and symbolic AI
Marwin H. S. Segler;Mike Preuss;Mark P. Waller.
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)
Sequential parameter optimization
T. Bartz-Beielstein;C.W.G. Lasarczyk;M. Preuss.
congress on evolutionary computation (2005)
Exploratory landscape analysis
Olaf Mersmann;Bernd Bischl;Heike Trautmann;Mike Preuss.
genetic and evolutionary computation conference (2011)
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)
Multiobjective exploration of the StarCraft map space
Julian Togelius;Mike Preuss;Nicola Beume;Simon Wessing.
computational intelligence and games (2010)
Multimodal Optimization by Means of a Topological Species Conservation Algorithm
C Stoean;M Preuss;R Stoean;D Dumitrescu.
IEEE Transactions on Evolutionary Computation (2010)
Towards multiobjective procedural map generation
Julian Togelius;Mike Preuss;Georgios N. Yannakakis.
foundations of digital games (2010)
Procedural Content Generation: Goals, Challenges and Actionable Steps
Julian Togelius;Alex J. Champandard;Pier Luca Lanzi;Michael Mateas.
computational intelligence and games (2013)
Capabilities of EMOA to detect and preserve equivalent pareto subsets
Günter Rudolph;Boris Naujoks;Mike Preuss.
international conference on evolutionary multi criterion optimization (2007)
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