Mike Preuss
Assistant professor
- Name
- Dr. M. Preuss
- Telephone
- +31 71 527 7492
- m.preuss@liacs.leidenuniv.nl
Mike Preuss is assistant professor at LIACS, the Computer Science department of Leiden University. He works in AI, namely game AI, natural computing, and social media computing.
Mike received his PhD in 2013 from the Chair of Algorithm Engineering at TU Dortmund, Germany, and was with ERCIS at the WWU Muenster, Germany, from 2013 to 2018. His research interests focus on the field of evolutionary algorithms for real-valued problems, namely on multi-modal and multi-objective optimization, and on computational intelligence and machine learning methods for computer games. Recently, he is also involved in Social Media Computing, and he is publications chair of the upcoming multi-disciplinary MISDOOM conference 2019. He is associate editor of the IEEE ToG journal and has been member of the organizational team of several conferences in the last years, in various functions, as general co-chair, proceedings chair, competition chair, workshops chair.
Assistant professor
- Wiskunde en Natuurwetenschappen
- Leiden Inst. Advanced Computer Sciences
- Wang H., Emmerich M.T.M., Preuss M. & Plaat A. (2020), Alternative Loss Functions in AlphaZero-like Self-play. In: 2019 IEEE Symposium Series on Computational Intelligence (SSCI).: IEEE. 155-162.
- Liapis A., Yannakakis G.N., Nelson M.J., Preuss M. & Bidarra R. (2019), Orchestrating Game Generation, IEEE Transactions on Games 11(1): 48-68.
- Wang H., Bäck T.H.W., Plaat A., Emmerich, M.T.M. & Preuss M. (2019), On the potential of evolution strategies for neural network weight optimization. In: Lopez-Ibanez M., Auger A., Stützle T. (Eds.) Proceedings of the Genetic and Evolutionary Computation Conference Companion.: ACM. 191-192.
- Kerschke P., Wang H., Preuss M., Grimme G., Deutz A.H., Trautmann H. & Emmerich M.T.M. (2019), Search Dynamics on Multimodal Multi-Objective Problems, Evolutionary Computation Journal 27(4): 577-609.
- Segler M.H.S, Preuss M. & Waller M.P. (2018), Planning chemical syntheses with deep neural networks and symbolic AI, Nature 555: 604-610.
- Schieb C. & Preuss M. (2018), Considering the Elaboration Likelihood Model for simulating hate and counter speech on Facebook, Studies in Communication and Media 7(4): 580-606.
- Pappa G.L., Emmerich M.T.M., Bazzan A., Browne W., Deb K., Doerr C., Ðurasević M., Epitropakis M.G., Haraldsson S.O., Jakobovic D., Kerschke P., Krawiec K., Lehre P.K., Li X., Lissovoi A., Malo P., Martí L., Mei Y., Merelo J.J., Miller J.F., Moraglio A., Nebro A.J., Nguyen S., Ochoa G., Oliveto P., Picek S., Pillay N., Preuss M., Schoenauer M., Senkerik R., Sinha A., Shir O., Sudholt D., Whitley D., Wineberg M., Woodward J. & Zhang M. (2018), Tutorials at PPSN 2018. In: Auger A., Fonseca C.M., Lourenço N., Machado P., Paquete L., Whitley D. (Eds.) International Conference on Parallel Problem Solving from Nature. no. Lecture Notes in Computer Science, volume 11102 Cham: Springer. 477-489.
- Grimme C., Preuss M., Adam L. & Trautmann H. (2017), Social Bots: Human-Like by Means of Human Control?, Big Data 5(4): 279-293.
- Ahrari A., Deb K. & Preuss M. (2017), Multimodal Optimization by Covariance Matrix Self-Adaptation Evolution Strategy with Repelling Subpopulations, Evolutionary Computation 25(3): 439-471.
- Buro M., Ontanon S. & Preuss M. (2016), Guest Editorial Real-Time Strategy Games, IEEE Transactions on Computational Intelligence and AI in Games 8(4): 317-318.
- Wessing S. & Preuss M. (2016), On multiobjective selection for multimodal optimization, Computational Optimization and Applications 63(3): 875-902.
- Mersmann O., Preuss M., Trautmann H., Bischl .B & Weihs C. (2015), Analyzing the BBOB Results by Means of Benchmarking Concepts, Evolutionary Computation 23(1): 161-185.
- Quadflieg J., Preuss M. & Rudolph G. (2014), Driving as a human: a track learning based adaptable architecture for a car racing controller, Genetic Programming and Evolvable Machines 15(4): 433-476.
- Ontanon S., Synnaeve G., Uriarte A., Richoux F., Churchill D. & Preuss M. (2013), A Survey of Real-Time Strategy Game AI Research and Competition in StarCraft, IEEE Transactions on Computational Intelligence and AI in Games 5(4): 293-311.
- Togelius J., Preuss M., Beume N., Wessing S., Hagelback J., Yannakakis G.N. & Grappiolo C. (2013), Controllable procedural map generation via multiobjective evolution, Genetic Programming and Evolvable Machines 14(2): 245-277.
- Vatolkin I., Preuss M., Rudolph G., Eichhoff M. & Weihs C. (2012), Multi-objective evolutionary feature selection for instrument recognition in polyphonic audio mixtures, Soft Computing 16(12): 2027-2047.
- Ochoa G., Preuss M., Bartz-Beielstein T. & Schoenauer M. (2012), Editorial for the Special Issue on Automated Design and Assessment of Heuristic Search Methods, Evolutionary Computation 20(2): 161-163.
- Stoean C., Preuss M., Stoean R. & Dumitrescu D. (2010), Multimodal Optimization by Means of a Topological Species Conservation Algorithm, IEEE Transactions on Evolutionary Computation 14(6): 842-864.
- Loiacono D., Lanzi P.L., Togelius J., Onieva E., Pelta D.A., Butz M.V., Lonneker T.D., Cardamone L., Perez D., Saez Y., Preuss M. & Quadflieg J. (2010), The 2009 Simulated Car Racing Championship, IEEE Transactions on Computational Intelligence and AI in Games 2(2): 131-147.
- Preuss M., Beume N., Danielsiek H., Hein T., Naujoks B., Piatkowski N., Stuer R., Thom A. & Wessing S. (2010), Towards Intelligent Team Composition and Maneuvering in Real-Time Strategy Games, IEEE Transactions on Computational Intelligence and AI in Games 2(2): 82-98.
- Trautmann H., Wagner T., Naujoks B., Preuss M. & Mehnen J. (2009), Statistical Methods for Convergence Detection of Multi-Objective Evolutionary Algorithms, Evolutionary Computation 17(4): 493-509.
- Stoean R., Preuss M., Stoean C., El-Darzi E. & Dumitrescu D. (2009), Support vector machine learning with an evolutionary engine, Journal of the Operational Research Society 60(8): 1116-1122.
- Stoean C., Preuss M. & Stoean R. (2009), Species Separation by a Clustering Mean towards Multimodal Function Optimization, Annals of the University of Craiova. Mathematics and Computer Science Series 36(2): 53-62.
- Henrich F., Bouvy C., Kausch C., Lucas K., Preuss M., Rudolph G. & Roosen P. (2008), Economic optimization of non-sharp separation sequences by means of evolutionary algorithms, Computers and Chemical Engineering 32(7): 1411-1432.
- Stoean C., Stoean R., Preuss M. & Dumitrescu D. (2006), A cooperative evolutionary algorithm for classification, International Journal of Computers Communications and Control 1(5): 417-422.
- Giacobini M., Preuss M. & Tomassini M. (2006), Effects of scale-free and small-world topologies on binary coded self-adaptive CEA. In: Gottlieb J., Raidl G.R. (Eds.) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2006. no. LNCS 3906 Berlin Heidelberg: Springer. 86-98.
- Stoean R., Stoean C., Preuss M. & Dumitrescu D. (2006), Evolutionary multi-class support vector machines for classification, International Journal of Computers Communications and Control 1(5): 423-428.
- Bartz-Beielstein T., Preuss M. & Rudolph G. (2006), Investigation of one-go evolution strategy/quasi-Newton hybridizations. In: Almeida F. (Ed.) Hybrid Metaheuristics. HM 2006. no. LNCS 4030 Berlin, Heidelberg: Springer. 178-191.
- Preuss M., Naujoks B. & Rudolph G. (2006), Pareto set and EMOA behavior for simple multimodal multiobjective functions. In: Runarsson T.P., Beyer H.G., Burke E., Merelo-Guervós J.J., Whitley L.D., Yao X. (Eds.) Parallel Problem Solving from Nature - PPSN IX. no. LNCS 4193 Berlin, Heidelberg: Springer. 513-522.
- Preuss M. & Lasarczyk C. (2004), On the importance of information speed in structured populations. In: Yao X. (Ed.) Parallel Problem Solving from Nature - PPSN VIII. PPSN 2004. no. 3242 Berlin, Heidelberg: Springer. 91-100.
- Jelasity M. & Preuss M. (2002), On obtaining global information in a peer-to-peer fully distributed environment. In: Monien B., Feldmann R. (Eds.) Euro-Par 2002 Parallel Processing. Euro-Par 2002. no. 2400 Berlin, Heidelberg: Springer. 573-577.
No relevant ancillary activities