Mike Preuss
Universitair hoofddocent
- Naam
- Dr. M. Preuss
- Telefoon
- +31 71 527 2727
- m.preuss@liacs.leidenuniv.nl
- ORCID iD
- 0000-0003-4681-1346
Mike Preuss is universitair hoofddocent aan het Leiden Institute of Advanced Computer Science aan de Universiteit Leiden. Hij is lid van het interdisciplinaire onderzoeksprogramma Society, Artificial Intelligence and Life Sciences (SAILS). Hij werkt aan kunstmatige intelligentie, voornamelijk game AI, natural computing en social media computing.
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Universitair hoofddocent
- Wiskunde en Natuurwetenschappen
- Leiden Inst of Advanced Computer Science
- Bernatavicius A., Sicho M., Janssen A.P.A., Hassen A.K., Preuss M. & Westen G.J.P. van (2024), AlphaFold Meets De Novo Drug Design: Leveraging Structural Protein Information in Multitarget Molecular Generative Models, Journal of Chemical Information and Modeling 64(21): 8113-8122.
- Plaat A., Kosters W.A. & Preuss M. (2023), High-accuracy model-based reinforcement learning, a survey, Artificial Intelligence Review 56: 9541-9573.
- Wang H., Emmerich M.T.M., Preuss M. & Plaat A. (2023), Analysis of hyper-parameters for AlphaZero-like deep reinforcement learning, International Journal of Information Technology and Decision Making 22(2): 829-853.
- Gómez-MaureiraA.: Kniestedt I. Barbero B. & Humain Preuss M. (2022), An explorer’s journal for machines: exploring the case of Cyberpunk 2077, Journal of Gaming & Virtual Worlds 14(1): 111-135.
- Yang Z., Preuss M. & Plaat A. (2022), Transfer learning and curriculum learning in Sokoban. Leiva L.A., PUrski C., Markovich R., Najjar A. & Schommer C. (red.), Artificial Intelligence and Machine Learning. BNAIC/Benelearn 2021.. Artificial Intelligence and Machine Learning - 33rd Benelux Conference on Artificial Intelligence, BNAIC/Benelearn 2021 10 november 2021 - 12 november 2021 nr. 1530. Cham: Springer. 187-200.
- Wang H., Preuss M., Emmerich M.T.M. & Plaat A. (2021), Tackling Morpion Solitaire with AlphaZero-like Ranked Reward Reinforcement Learning, 2020 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC). 2nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) 1 september 2020 - 4 september 2020: IEEE. 149-152.
- Wang H., Preuss M. & Plaat A. (2021), Adaptive warm-start MCTS in AlphaZero-like deep reinforcement learning. Pham D.N., Theeramunkong T., Governatori G. & Liu F. (red.), PRICAI 2021: Trends in artificial intelligence. Pacific Rim International Conference on Artificial Intelligence 2021 8 november 2021 - 12 november 2021 nr. LNCS-13033. Cham: Springer. 60-71.
- Müller-Brockhausen M.F.T., Preuss M. & Plaat A. (2021), A new challenge: approaching Tetris Link with AI, 2021 IEEE Conference on games (CoG). IEEE Conference on Games 17 augustus 2021 - 20 augustus 2021. Copenhagen: IEEE.
- Müller-Brockhausen M.F.T., Preuss M. & Plaat A. (2021), Procedural content generation: better benchmarks for transfer reinforcement learning, 2021 IEEE Conference on games (CoG). IEEE Conference on Games 17 augustus 2021 - 20 augustus 2021. Copenhagen: IEEE.
- Grimme C., Kerschke P., Aspar P., Trautmann H., Preuss M., Deutz A.H., Wang H. & Emmerich M.T.M. (2021), Peeking beyond peaks: challenges and research potentials of continuous multimodal multi-objective optimization, Computers & Operations Research 136: 105489.
- Mozgovoy M., Preuss M. & Bidarra R. (2021), Team sports for game AI benchmarking revisited, International Journal of Computer Games Technology 2021: 1-9 (5521877 ).
- Rothmeier K., Pflanzl N., Hullmann J.A. & Preuss M. (2021), Prediction of player churn and disengagement based on user activity data of a freemium online strategy game, IEEE Transactions on Games 13(1): 78-88.
- Luo W., Lin X., Zhang J. & Preuss M. (2021), A survey of nearest-better clustering in swarm and evolutionary computation, 2021 IEEE Congress on Evolutionary Computation (CEC). IEEE Congress on Evolutionary Computation, CEC 2021 28 juni 2021 - 1 juli 2021: IEEE. 1961-1967.
- Gómez Maureira M.A., Barbero G., Freese M. & Preuss M. (2020), Towards a taxonomy of AI in hybrid board games. Yannakakis G.N., Liapis A., Kyburz P., Volz V., Khosmood F. & Lopes P. (red.), FDG '20: Proceedings of the 15th international conference on the foundations of digital games. FDG '20: International Conference on the Foundations of Digital Games 15 september 2020 - 18 september 2020. New York, U.S.A.: Association for Computing Machinery.
- Wang H., Emmerich M.T.M., Preuss M. & Plaat A. (2020), Alternative loss functions in AlphaZero-like self-play, 2019 IEEE Symposium Series on Computational Intelligence (SSCI). 2019 IEEE Symposium Series on Computational Intelligence (SSCI) 6 december 2019 - 9 december 2019: IEEE. 155-162.
- Duijn M. van, Preuss M., Spaiser V., Takes F.W. & Verberne S. (red.) (2020), Disinformation in Open Online Media. Lecture Notes in Computer Science nr. 12259. Cham: Springer.
- Wang H., Preuss M. & Plaat A. (2020), Warm-start AlphaZero self-play search enhancements. Bäck T.W., Preuss M., Deutz A., Wang H., Doerr C., Emmerich M.T.M. & Trautmann H. (red.), Parallel Problem Solving from Nature – PPSN XVI. PPSN 2020. PPSN 2020 (16th International Conference on Parallel Problem Solving from Nature) 5 september 2020 - 9 september 2020 nr. Lecture Notes in Computer Science, vol. 12270. Cham: Springer. 528-542.
- Hagg A., Preuss M., Asteroth A. & Bäck T.H.W. (2020), An analysis of phenotypic diversity in multi-solution optimization. Filipič B., Minisci E. & Vasile M. (red.), International Conference on Bioinspired Methods and Their Applications. 9th International Conference, BIOMA 2020 19 november 2020 - 20 november 2020. Cham: Springer. 43-55.
- Virag D., Offerman T.D., Jong B. de & Preuss M. (2020), IT security challenges for continuously connected near-autonomous vehicles, 2020 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC). 2020 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) 15 juni 2020 - 17 juni 2020: IEEE. 1-8.
- 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. Lopez-Ibanez M., Auger A. & Stützle T. (red.), Proceedings of the Genetic and Evolutionary Computation Conference Companion. GECCO 2019 13 juli 2019 - 17 juli 2019: 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 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.
- 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. Auger A., Fonseca C.M., Lourenço N., Machado P., Paquete L. & Whitley D. (red.), International Conference on Parallel Problem Solving from Nature. PPSN: International Conference on Parallel Solving from Nature 8 september 2018 - 12 september 2018 nr. Lecture Notes in Computer Science, volume 11102. Cham: Springer. 477-489.
- 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.
- 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.
- Grimme C., Preuss M., Adam L. & Trautmann H. (2017), Social Bots: Human-Like by Means of Human Control?, Big Data 5(4): 279-293.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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 & 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. Gottlieb J. & Raidl G.R. (red.), Evolutionary Computation in Combinatorial Optimization. EvoCOP 2006. European Conference on Evolutionary Computation in Combinatorial Optimization 10 april 2006 - 12 april 2019 nr. 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. Almeida F. (red.), Hybrid Metaheuristics. HM 2006. Hybrid Metaheuristics 2006 13 oktober 2006 - 14 oktober 2006 nr. LNCS 4030. Berlin, Heidelberg: Springer. 178-191.
- Preuss M., Naujoks B. & Rudolph G. (2006), Pareto set and EMOA behavior for simple multimodal multiobjective functions. Runarsson T.P., Beyer H.G., Burke E., Merelo-Guervós J.J., Whitley L.D. & Yao X. (red.), Parallel Problem Solving from Nature - PPSN IX. Problem Solving from Nature 9 september 2006 - 13 september 2006 nr. LNCS 4193. Berlin, Heidelberg: Springer. 513-522.
- Preuss M. & Lasarczyk C. (2004), On the importance of information speed in structured populations. Yao X. (red.), Parallel Problem Solving from Nature - PPSN VIII. PPSN 2004. Parallel Problem Solving from Nature 18 september 2004 - 22 februari 2019 nr. 3242. Berlin, Heidelberg: Springer. 91-100.
- Jelasity M. & Preuss M. (2002), On obtaining global information in a peer-to-peer fully distributed environment. Monien B. & Feldmann R. (red.), Euro-Par 2002 Parallel Processing. Euro-Par 2002. Congress on Evolutionary Computation. CEC'02 12 mei 2002 - 17 februari 2019 nr. 2400. Berlin, Heidelberg: Springer. 573-577.