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ORCIDMike Preuss
Mike Preuß
Person information
- affiliation: Universiteit Leiden, The Netherlands
- affiliation (former): WWU Münster, Germany
- affiliation (former): Technical University of Dortmund, Germany
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Books and Theses
- 2015
[b1]Mike Preuss:
Multimodal Optimization by Means of Evolutionary Algorithms. Natural Computing Series, Springer 2015, ISBN 978-3-319-07406-1, pp. 1-175
Journal Articles
- 2024
- [j33]Manuel López-Ibáñez
, Luís Paquete, Mike Preuss:
Editorial for the Special Issue on Reproducibility. Evol. Comput. 32(1): 1-2 (2024) - 2023
- [j32]Aske Plaat, Walter A. Kosters, Mike Preuss:
High-accuracy model-based reinforcement learning, a survey. Artif. Intell. Rev. 56(9): 9541-9573 (2023) - [j31]Hui Wang, Michael Emmerich, Mike Preuss, Aske Plaat:
Analysis of Hyper-Parameters for AlphaZero-Like Deep Reinforcement Learning. Int. J. Inf. Technol. Decis. Mak. 22(2): 829-853 (2023) - 2022
- [j30]Wenjian Luo, Yingying Qiao, Xin Lin, Peilan Xu, Mike Preuss:
Hybridizing Niching, Particle Swarm Optimization, and Evolution Strategy for Multimodal Optimization. IEEE Trans. Cybern. 52(7): 6707-6720 (2022) - 2021
- [j29]Christian Grimme, Pascal Kerschke, Pelin Aspar, Heike Trautmann, Mike Preuss, André H. Deutz, Hao Wang, Michael Emmerich:
Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. Comput. Oper. Res. 136: 105489 (2021) - [j28]Maxim Mozgovoy, Mike Preuss, Rafael Bidarra:
Team Sports for Game AI Benchmarking Revisited. Int. J. Comput. Games Technol. 2021: 5521877:1-5521877:9 (2021) - [j27]Karsten Rothmeier, Nicolas Pflanzl, Joschka Andreas Hüllmann, Mike Preuss:
Prediction of Player Churn and Disengagement Based on User Activity Data of a Freemium Online Strategy Game. IEEE Trans. Games 13(1): 78-88 (2021) - [j26]Maxim Mozgovoy, Mike Preuss, Rafael Bidarra:
Guest Editorial Special Issue on Team AI in Games. IEEE Trans. Games 13(4): 327-329 (2021) - 2020
- [j25]Sebastian Risi, Mike Preuss:
Special Issue on AI in Games. Künstliche Intell. 34(1): 5-6 (2020) - [j24]Sebastian Risi, Mike Preuss:
From Chess and Atari to StarCraft and Beyond: How Game AI is Driving the World of AI. Künstliche Intell. 34(1): 7-17 (2020) - [j23]Mike Preuss, Sebastian Risi:
A Games Industry Perspective on Recent Game AI Developments. Künstliche Intell. 34(1): 81-83 (2020) - [j22]Sebastian Risi, Mike Preuss:
Behind DeepMind's AlphaStar AI that Reached Grandmaster Level in StarCraft II. Künstliche Intell. 34(1): 85-86 (2020) - 2019
- [j21]Pascal Kerschke, Hao Wang, Mike Preuss, Christian Grimme, André H. Deutz, Heike Trautmann, Michael T. M. Emmerich:
Search Dynamics on Multimodal Multiobjective Problems. Evol. Comput. 27(4): 577-609 (2019) - [j20]Antonios Liapis, Georgios N. Yannakakis, Mark J. Nelson, Mike Preuss, Rafael Bidarra:
Orchestrating Game Generation. IEEE Trans. Games 11(1): 48-68 (2019) - 2018
- [j19]Marwin H. S. Segler, Mike Preuss, Mark P. Waller:
Planning chemical syntheses with deep neural networks and symbolic AI. Nat. 555(7698): 604-610 (2018) - 2017
- [j18]Christian Grimme, Mike Preuss, Lena Adam, Heike Trautmann:
Social Bots: Human-Like by Means of Human Control? Big Data 5(4): 279-293 (2017) - [j17]Ali Ahrari, Kalyanmoy Deb, Mike Preuss:
Multimodal Optimization by Covariance Matrix Self-Adaptation Evolution Strategy with Repelling Subpopulations. Evol. Comput. 25(3): 439-471 (2017) - 2016
- [j16]Simon Wessing, Mike Preuss:
On multiobjective selection for multimodal optimization. Comput. Optim. Appl. 63(3): 875-902 (2016) - [j15]Michael Buro, Santiago Ontañón, Mike Preuss:
Guest Editorial Real-Time Strategy Games. IEEE Trans. Comput. Intell. AI Games 8(4): 317-318 (2016) - 2015
- [j14]Mike Preuss, Günter Rudolph:
Conference Report on IEEE CIG 2014 [Conference Reports]. IEEE Comput. Intell. Mag. 10(1): 14-15 (2015) - [j13]Olaf Mersmann, Mike Preuss, Heike Trautmann, Bernd Bischl, Claus Weihs:
Analyzing the BBOB Results by Means of Benchmarking Concepts. Evol. Comput. 23(1): 161-185 (2015) - 2014
- [j12]Jan Quadflieg, Mike Preuss, Günter Rudolph:
Driving as a human: a track learning based adaptable architecture for a car racing controller. Genet. Program. Evolvable Mach. 15(4): 433-476 (2014) - 2013
- [j11]Julian Togelius, Mike Preuss, Nicola Beume, Simon Wessing, Johan Hagelbäck, Georgios N. Yannakakis, Corrado Grappiolo:
Controllable procedural map generation via multiobjective evolution. Genet. Program. Evolvable Mach. 14(2): 245-277 (2013) - [j10]Santiago Ontañón, Gabriel Synnaeve, Alberto Uriarte, Florian Richoux, David Churchill, Mike Preuss:
A Survey of Real-Time Strategy Game AI Research and Competition in StarCraft. IEEE Trans. Comput. Intell. AI Games 5(4): 293-311 (2013) - 2012
- [j9]Gabriela Ochoa, Mike Preuss, Thomas Bartz-Beielstein, Marc Schoenauer:
Editorial for the Special Issue on Automated Design and Assessment of Heuristic Search Methods. Evol. Comput. 20(2): 161-163 (2012) - [j8]Igor Vatolkin, Mike Preuß, Günter Rudolph, Markus Eichhoff, Claus Weihs:
Multi-objective evolutionary feature selection for instrument recognition in polyphonic audio mixtures. Soft Comput. 16(12): 2027-2047 (2012) - 2010
- [j7]Mike Preuss, Nicola Beume, Holger Danielsiek, Tobias Hein, Boris Naujoks, Nico Piatkowski, Raphael Stür, Andreas Thom, Simon Wessing:
Towards Intelligent Team Composition and Maneuvering in Real-Time Strategy Games. IEEE Trans. Comput. Intell. AI Games 2(2): 82-98 (2010) - [j6]Daniele Loiacono, Pier Luca Lanzi, Julian Togelius, Enrique Onieva, David A. Pelta, Martin V. Butz, Thies D. Lönneker, Luigi Cardamone, Diego Perez Liebana, Yago Sáez, Mike Preuss, Jan Quadflieg:
The 2009 Simulated Car Racing Championship. IEEE Trans. Comput. Intell. AI Games 2(2): 131-147 (2010) - [j5]Catalin Stoean, Mike Preuss, Ruxandra Stoean, Dumitru Dumitrescu:
Multimodal Optimization by Means of a Topological Species Conservation Algorithm. IEEE Trans. Evol. Comput. 14(6): 842-864 (2010) - 2009
- [j4]Heike Trautmann, Tobias Wagner, Boris Naujoks, Mike Preuß, Jörn Mehnen:
Statistical Methods for Convergence Detection of Multi-Objective Evolutionary Algorithms. Evol. Comput. 17(4): 493-509 (2009) - [j3]Ruxandra Stoean, Mike Preuss, Catalin Stoean, Elia El-Darzi, D. Dumitrescu:
Support vector machine learning with an evolutionary engine. J. Oper. Res. Soc. 60(8): 1116-1122 (2009) - 2008
- [j2]Frank Henrich, Claude Bouvy, Christoph Kausch, Klaus Lucas, Mike Preuß, Günter Rudolph, Peter Roosen:
Economic optimization of non-sharp separation sequences by means of evolutionary algorithms. Comput. Chem. Eng. 32(7): 1411-1432 (2008) - 2004
- [j1]Lutz Schönemann, Michael Emmerich, Mike Preuss:
On the Extinction of Evolutionary Algorithm Subpopulations on Multimodal Landscapes. Informatica (Slovenia) 28(4): 345-351 (2004)
Conference and Workshop Papers
- 2023
- [c127]Matthias Müller-Brockhausen, Giulio Barbero, Mike Preuss:
Chatter Generation through Language Models. CoG 2023: 1-6 - [c126]Arthur van der Staaij, Jelmer Prins, Vincent L. Prins, Julian Poelsma, Thera Smit, Matthias Müller-Brockhausen, Mike Preuss:
Believable Minecraft Settlements by Means of Decentralised Iterative Planning. CoG 2023: 1-8 - [c125]Zhao Yang, Thomas M. Moerland, Mike Preuss, Aske Plaat:
Continuous Episodic Control. CoG 2023: 1-8 - [c124]Zhao Yang, Thomas M. Moerland, Mike Preuss, Aske Plaat:
Two-Memory Reinforcement Learning. CoG 2023: 1-9 - [c123]Vincent L. Prins, Jelmer Prins, Mike Preuss, Marcello A. Gómez Maureira:
StoryWorld: Procedural Quest Generation Rooted in Variety & Believability. FDG 2023: 44:1-44:4 - [c122]Suzan Al-Nassar, Anthonie Schaap, Michael Van Der Zwart, Mike Preuss, Marcello A. Gómez Maureira:
QuestVille: Procedural Quest Generation Using NLP Models. FDG 2023: 50:1-50:4 - [c121]Antonios Liapis, Christian Guckelsberger, Jichen Zhu, Casper Harteveld, Simone Kriglstein, Alena Denisova, Jeremy Gow, Mike Preuss:
Designing for Playfulness in Human-AI Authoring Tools. FDG 2023: 75:1-75:4 - [c120]Pascal Kerschke, Mike Preuss:
Exploratory Landscape Analysis. GECCO Companion 2023: 990-1007 - [c119]Zhao Yang, Thomas M. Moerland, Mike Preuss, Aske Plaat:
First Go, then Post-Explore: The Benefits of Post-Exploration in Intrinsic Motivation. ICAART (2) 2023: 27-34 - [c118]Marco Pleines, Matthias Pallasch, Frank Zimmer, Mike Preuss:
Memory Gym: Partially Observable Challenges to Memory-Based Agents. ICLR 2023 - 2022
- [c117]Matthias Müller-Brockhausen, Aske Plaat, Mike Preuss:
Towards verifiable Benchmarks for Reinforcement Learning. CoG 2022: 159-166 - [c116]Marco Pleines, Konstantin Ramthun, Yannik Wegener, Hendrik Meyer, Matthias Pallasch, Sebastian Prior, Jannik Drögemüller, Leon Büttinghaus, Thilo Röthemeyer, Alexander Kaschwig, Oliver Chmurzynski, Frederik Rohkrähmer, Roman Kalkreuth, Frank Zimmer, Mike Preuss:
On the Verge of Solving Rocket League using Deep Reinforcement Learning and Sim-to-sim Transfer. CoG 2022: 253-260 - [c115]Christoph Salge, Claus Aranha, Adrian Brightmoore, Sean Butler, Rodrigo De Moura Canaan, Michael Cook, Michael Cerny Green, Hagen Fischer, Christian Guckelsberger, Jupiter Hadley, Jean-Baptiste Hervé, Mark Richard Johnson, Quinn Kybartas, David Mason, Mike Preuss, Tristan Smith, Ruck Thawonmas, Julian Togelius:
Impressions of the GDMC AI Settlement Generation Challenge in Minecraft. FDG 2022: 45:1-45:16 - [c114]Christian Grimme, Janina Pohl, Stefano Cresci, Ralf Lüling, Mike Preuss:
New Automation for Social Bots: From Trivial Behavior to AI-Powered Communication. MISDOOM 2022: 79-99 - 2021
- [c113]Zhao Yang, Mike Preuss, Aske Plaat:
Transfer Learning and Curriculum Learning in Sokoban. BNAIC/BENELEARN 2021: 187-200 - [c112]Wenjian Luo, Xin Lin, Jiajia Zhang, Mike Preuss:
A Survey of Nearest-Better Clustering in Swarm and Evolutionary Computation. CEC 2021: 1961-1967 - [c111]Matthias Müller-Brockhausen, Mike Preuss, Aske Plaat:
A New Challenge: Approaching Tetris Link with AI. CoG 2021: 1-8 - [c110]Matthias Müller-Brockhausen, Mike Preuss, Aske Plaat:
Procedural Content Generation: Better Benchmarks for Transfer Reinforcement Learning. CoG 2021: 1-8 - [c109]Hui Wang, Mike Preuss, Aske Plaat:
Adaptive Warm-Start MCTS in AlphaZero-Like Deep Reinforcement Learning. PRICAI (3) 2021: 60-71 - 2020
- [c108]Alexander Hagg, Mike Preuss, Alexander Asteroth, Thomas Bäck:
An Analysis of Phenotypic Diversity in Multi-solution Optimization. BIOMA 2020: 43-55 - [c107]Marco Pleines, Jenia Jitsev, Mike Preuss, Frank Zimmer:
Obstacle Tower Without Human Demonstrations: How Far a Deep Feed-Forward Network Goes with Reinforcement Learning. CoG 2020: 447-454 - [c106]Christoph Salge, Emily Short, Mike Preuss, Spyridon Samothrakis, Pieter Spronck:
Applications of Artificial Intelligence in Live Action Role-Playing Games (LARP). CoG 2020: 612-619 - [c105]Marcello A. Gómez Maureira, Giulio Barbero, Maria Freese, Mike Preuss:
Towards a Taxonomy of AI in Hybrid Board Games. FDG 2020: 105:1-105:6 - [c104]Jialin Liu, Antoine Moreau, Mike Preuss, Jérémy Rapin, Baptiste Rozière, Fabien Teytaud, Olivier Teytaud:
Versatile black-box optimization. GECCO 2020: 620-628 - [c103]Christian Stöcker, Mike Preuss:
Riding the Wave of Misclassification: How We End up with Extreme YouTube Content. HCI (14) 2020: 359-375 - [c102]David Virag, Tyron Offerman, Bart de Jong, Mike Preuss:
IT security challenges for continuously connected near-autonomous vehicles. ICE/ITMC 2020: 1-8 - [c101]Lena Clever, Dennis Assenmacher, Kilian Müller, Moritz Vinzent Seiler, Dennis M. Riehle, Mike Preuss, Christian Grimme:
FakeYou! - A Gamified Approach for Building and Evaluating Resilience Against Fake News. MISDOOM 2020: 218-232 - [c100]Hui Wang, Mike Preuss, Aske Plaat:
Warm-Start AlphaZero Self-play Search Enhancements. PPSN (2) 2020: 528-542 - [c99]Yannick Verhoeven, Mike Preuss:
On the Potential of Rocket League for Driving Team AI Development. SSCI 2020: 2335-2342 - [c98]Hui Wang, Mike Preuss, Michael Emmerich, Aske Plaat:
Tackling Morpion Solitaire with AlphaZero-like Ranked Reward Reinforcement Learning. SYNASC 2020: 149-152 - 2019
- [c97]Raphael Patrick Prager, Laura Troost, Simeon Brüggenjürgen, David Melhart, Georgios N. Yannakakis, Mike Preuss:
An Experiment on Game Facet Combination\. CoG 2019: 1-8 - [c96]Hao Wang, Thomas Bäck, Aske Plaat, Michael Emmerich, Mike Preuss:
On the potential of evolution strategies for neural network weight optimization. GECCO (Companion) 2019: 191-192 - [c95]Pascal Kerschke, Mike Preuss:
Exploratory landscape analysis. GECCO (Companion) 2019: 1137-1155 - [c94]Jérémy Rapin, Marcus Gallagher, Pascal Kerschke, Mike Preuss, Olivier Teytaud:
Exploring the MLDA benchmark on the nevergrad platform. GECCO (Companion) 2019: 1888-1896 - [c93]Hui Wang, Michael Emmerich, Mike Preuss, Aske Plaat:
Alternative Loss Functions in AlphaZero-like Self-play. SSCI 2019: 155-162 - [c92]Wenjian Luo, Yingying Qiao, Xin Lin, Peilan Xu, Mike Preuss:
Many-Modal Optimization by Difficulty-Based Cooperative Co-evolution. SSCI 2019: 1907-1914 - 2018
- [c91]Mike Preuss, Thomas Pfeiffer, Vanessa Volz, Nicolas Pflanzl:
Integrated Balancing of an RTS Game: Case Study and Toolbox Refinement. CIG 2018: 1-8 - [c90]Vanessa Volz, Kevin Majchrzak, Mike Preuss:
A Social Science-based Approach to Explanations for (Game) AI. CIG 2018: 1-2 - [c89]Vanessa Volz, Mike Preuss, Mathias Kirk Bonde:
Towards Embodied StarCraft II Winner Prediction. CGW@IJCAI 2018: 3-22 - [c88]Gisele Lobo Pappa, Michael T. M. Emmerich, Ana L. C. Bazzan, Will N. Browne, Kalyanmoy Deb, Carola Doerr, Marko Durasevic, Michael G. Epitropakis, Saemundur O. Haraldsson, Domagoj Jakobovic, Pascal Kerschke, Krzysztof Krawiec, Per Kristian Lehre, Xiaodong Li, Andrei Lissovoi, Pekka Malo, Luis Martí, Yi Mei, Juan Julián Merelo Guervós, Julian F. Miller, Alberto Moraglio, Antonio J. Nebro, Su Nguyen, Gabriela Ochoa, Pietro S. Oliveto, Stjepan Picek, Nelishia Pillay, Mike Preuss, Marc Schoenauer, Roman Senkerik, Ankur Sinha, Ofer M. Shir, Dirk Sudholt, L. Darrell Whitley, Mark Wineberg, John R. Woodward, Mengjie Zhang:
Tutorials at PPSN 2018. PPSN (2) 2018: 477-489 - [c87]Robin C. Purshouse, Christine Zarges, Sylvain Cussat-Blanc, Michael G. Epitropakis, Marcus Gallagher, Thomas Jansen, Pascal Kerschke, Xiaodong Li, Fernando G. Lobo, Julian F. Miller, Pietro S. Oliveto, Mike Preuss, Giovanni Squillero, Alberto Paolo Tonda, Markus Wagner, Thomas Weise, Dennis Wilson, Borys Wróbel, Ales Zamuda:
Workshops at PPSN 2018. PPSN (2) 2018: 490-497 - 2017
- [c86]Ahmed Khalifa, Mike Preuss, Julian Togelius:
Multi-objective Adaptation of a Parameterized GVGAI Agent Towards Several Games. EMO 2017: 359-374 - [c85]Pascal Kerschke, Mike Preuss:
Exploratory landscape analysis: advanced tutorial at GECCO 2017. GECCO (Companion) 2017: 762-781 - [c84]Marwin H. S. Segler, Mike Preuss, Mark P. Waller:
Towards "AlphaChem": Chemical Synthesis Planning with Tree Search and Deep Neural Network Policies. ICLR (Workshop) 2017 - [c83]Simon Wessing, Mike Preuss:
The true destination of EGO is multi-local optimization. LA-CCI 2017: 1-6 - 2016
- [c82]Marlene Beyer, Aleksandr Agureikin, Alexander Anokhin, Christoph Laenger, Felix Nolte, Jonas Winterberg, Marcel Renka, Martin Rieger, Nicolas Pflanzl, Mike Preuss, Vanessa Volz:
An integrated process for game balancing. CIG 2016: 1-8 - [c81]Hendrik Horn, Vanessa Volz, Diego Perez Liebana, Mike Preuss:
MCTS/EA hybrid GVGAI players and game difficulty estimation. CIG 2016: 1-8 - [c80]Pascal Kerschke, Mike Preuss, Simon Wessing, Heike Trautmann:
Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models. GECCO 2016: 229-236 - [c79]Pascal Kerschke, Hao Wang, Mike Preuss, Christian Grimme, André H. Deutz, Heike Trautmann, Michael Emmerich:
Towards Analyzing Multimodality of Continuous Multiobjective Landscapes. PPSN 2016: 962-972 - [c78]Carola Doerr, Nicolas Bredèche, Enrique Alba, Thomas Bartz-Beielstein, Dimo Brockhoff, Benjamin Doerr, Gusz Eiben, Michael G. Epitropakis, Carlos M. Fonseca, Andreia P. Guerreiro, Evert Haasdijk, Jacqueline Heinerman, Julien Hubert, Per Kristian Lehre, Luigi Malagò, Juan Julián Merelo Guervós, Julian Francis Miller, Boris Naujoks, Pietro S. Oliveto, Stjepan Picek, Nelishia Pillay, Mike Preuss, Patricia Ryser-Welch, Giovanni Squillero, Jörg Stork, Dirk Sudholt, Alberto Paolo Tonda, L. Darrell Whitley, Martin Zaefferer:
Tutorials at PPSN 2016. PPSN 2016: 1012-1022 - 2015
- [c77]David Stammer, Tobias Günther, Mike Preuss:
Player-adaptive Spelunky level generation. CIG 2015: 130-137 - [c76]Jan Quadflieg, Günter Rudolph, Mike Preuss:
How costly is a good compromise: Multi-objective TORCS controller parameter optimization. CIG 2015: 454-460 - [c75]Pascal Kerschke, Mike Preuss, Simon Wessing, Heike Trautmann:
Detecting Funnel Structures by Means of Exploratory Landscape Analysis. GECCO 2015: 265-272 - [c74]Mike Preuss:
Multimodal Optimization. GECCO (Companion) 2015: 293-312 - 2014
- [c73]Mike Preuss, Antonios Liapis, Julian Togelius:
Searching for good and diverse game levels. CIG 2014: 1-8 - [c72]Mike Preuss, Philip Voll, André Bardow, Günter Rudolph:
Looking for Alternatives: Optimization of Energy Supply Systems without Superstructure. EvoApplications 2014: 177-188 - [c71]Paolo Burelli, Mike Preuss:
Automatic Camera Control: A Dynamic Multi-Objective Perspective. EvoApplications 2014: 361-373 - [c70]Simon Wessing, Mike Preuss, Heike Trautmann:
Stopping Criteria for Multimodal Optimization. PPSN 2014: 141-150 - 2013
- [c69]Simon Wessing, Mike Preuss, Günter Rudolph:
Niching by multiobjectivization with neighbor information: Trade-offs and benefits. IEEE Congress on Evolutionary Computation 2013: 103-110 - [c68]Matthias Kuchem, Mike Preuss, Günter Rudolph:
Multi-objective assessment of pre-optimized build orders exemplified for StarCraft 2. CIG 2013: 1-8 - [c67]Mike Preuss, Daniel Kozakowski, Johan Hagelbäck, Heike Trautmann:
Reactive strategy choice in StarCraft by means of Fuzzy Control. CIG 2013: 1-8 - [c66]Daniele Loiacono, Mike Preuss:
Computational intelligence and games. GECCO (Companion) 2013: 957-978 - [c65]Catalin Stoean, Mike Preuss, Ruxandra Stoean:
EA-based parameter tuning of multimodal optimization performance by means of different surrogate models. GECCO (Companion) 2013: 1063-1070 - 2012
- [c64]Annika Jordan, Dimitri Scheftelowitsch, Jan Lahni, Jannic Hartwecker, Matthias Kuchem, Mirko Walter-Huber, Nils Vortmeier, Tim Delbrügger, Ümit Güler, Igor Vatolkin, Mike Preuss:
BeatTheBeat music-based procedural content generation in a mobile game. CIG 2012: 320-327 - [c63]Mike Preuss, Paolo Burelli, Georgios N. Yannakakis:
Diversified Virtual Camera Composition. EvoApplications 2012: 265-274 - [c62]Mike Preuss:
Improved Topological Niching for Real-Valued Global Optimization. EvoApplications 2012: 386-395 - [c61]Bernd Bischl, Olaf Mersmann, Heike Trautmann, Mike Preuß:
Algorithm selection based on exploratory landscape analysis and cost-sensitive learning. GECCO 2012: 313-320 - [c60]Daniele Loiacono, Mike Preuß:
Computational intelligence in games. GECCO (Companion) 2012: 1139-1140 - [c59]Thomas Bartz-Beielstein, Mike Preuß, Martin Zaefferer:
Statistical analysis of optimization algorithms with R. GECCO (Companion) 2012: 1259-1286 - [c58]Mike Preuss, Tobias Wagner, David Ginsbourger:
High-Dimensional Model-Based Optimization Based on Noisy Evaluations of Computer Games. LION 2012: 145-159 - 2011
- [c57]Philip Hingston, Mike Preuss:
Red teaming with coevolution. IEEE Congress on Evolutionary Computation 2011: 1155-1163 - [c56]Mike Preuss, Jan Quadflieg, Günter Rudolph:
TORCS sensor noise removal and multi-objective track selection for driving style adaptation. CIG 2011: 337-344 - [c55]Robert G. Reynolds, Daniel A. Ashlock, Georgios N. Yannakakis, Julian Togelius, Mike Preuss:
Tutorials: Cultural Algorithms: Incorporating social intelligence into virtual worlds. CIG 2011 - [c54]Markus Kemmerling, Niels Ackermann, Mike Preuss:
Nested Look-Ahead Evolutionary Algorithm Based Planning for a Believable Diplomacy Bot. EvoApplications (1) 2011: 83-92 - [c53]Jan Quadflieg, Mike Preuss, Günter Rudolph:
Driving Faster Than a Human Player. EvoApplications (1) 2011: 143-152 - [c52]Igor Vatolkin, Mike Preuß, Günter Rudolph:
Multi-objective feature selection in music genre and style recognition tasks. GECCO 2011: 411-418 - [c51]Simon Wessing, Mike Preuss, Günter Rudolph:
When parameter tuning actually is parameter control. GECCO 2011: 821-828 - [c50]Olaf Mersmann, Bernd Bischl, Heike Trautmann, Mike Preuss, Claus Weihs, Günter Rudolph:
Exploratory landscape analysis. GECCO 2011: 829-836 - [c49]Mike Preuss, Catalin Stoean, Ruxandra Stoean:
Niching foundations: basin identification on fixed-property generated landscapes. GECCO 2011: 837-844 - [c48]Thomas Bartz-Beielstein, Mike Preuss:
Automatic and interactive tuning of algorithms. GECCO (Companion) 2011: 1361-1380 - 2010
- [c47]Philip Hingston, Mike Preuss, Daniel Spierling:
RedTNet: A network model for strategy games. IEEE Congress on Evolutionary Computation 2010: 1-9 - [c46]Johan Hagelbäck, Stefan J. Johansson, Mike Preuss:
AI and computational intelligence for real-time strategy games. CIG 2010: 1-4 - [c45]Markus Kemmerling, Mike Preuss:
Automatic adaptation to generated content via car setup optimization in TORCS. CIG 2010: 131-138 - [c44]Julian Togelius, Mike Preuss, Nicola Beume, Simon Wessing, Johan Hagelbäck, Georgios N. Yannakakis:
Multiobjective exploration of the StarCraft map space. CIG 2010: 265-272 - [c43]Jan Quadflieg, Mike Preuss, Oliver Kramer, Günter Rudolph:
Learning the track and planning ahead in a car racing controller. CIG 2010: 395-402 - [c42]Julian Togelius, Mike Preuss, Georgios N. Yannakakis:
Towards multiobjective procedural map generation. PCGames@FDG 2010: 3:1-3:8 - [c41]Mike Preuss, Günter Rudolph, Simon Wessing:
Tuning optimization algorithms for real-world problems by means of surrogate modeling. GECCO 2010: 401-408 - [c40]Mike Preuss:
Niching the CMA-ES via nearest-better clustering. GECCO (Companion) 2010: 1711-1718 - [c39]Thomas Bartz-Beielstein, Mike Preuss:
Tuning and experimental analysis in evolutionary computation: what we still have wrong. GECCO (Companion) 2010: 2625-2646 - [c38]Olaf Mersmann, Mike Preuss, Heike Trautmann:
Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis. PPSN (1) 2010: 73-82 - [c37]Bernd Bischl, Igor Vatolkin, Mike Preuss:
Selecting Small Audio Feature Sets in Music Classification by Means of Asymmetric Mutation. PPSN (1) 2010: 314-323 - 2009
- [c36]Markus Kemmerling, Niels Ackermann, Nicola Beume, Mike Preuss, Sebastian Uellenbeck, Wolfgang Walz:
Is human-like and well playing contradictory for Diplomacy bots? CIG 2009: 209-216 - [c35]Günter Rudolph, Mike Preuss:
A multiobjective approach for finding equivalent inverse images of Pareto-optimal objective vectors. MCDM 2009: 74-79 - [c34]Nicola Beume, Boris Naujoks, Mike Preuss, Günter Rudolph, Tobias Wagner:
Effects of 1-Greedy -Metric-Selection on Innumerably Large Pareto Fronts. EMO 2009: 21-35 - [c33]Ofer M. Shir, Mike Preuss, Boris Naujoks, Michael T. M. Emmerich:
Enhancing Decision Space Diversity in Evolutionary Multiobjective Algorithms. EMO 2009: 95-109 - [c32]Mike Preuss:
Adaptability of Algorithms for Real-Valued Optimization. EvoWorkshops 2009: 665-674 - [c31]Thomas Bartz-Beielstein, Mike Preuss:
the future of experimental research. GECCO (Companion) 2009: 3185-3226 - 2008
- [c30]Nicola Beume, Holger Danielsiek, Christian Eichhorn, Boris Naujoks, Mike Preuss, Klaus D. Stiller, Simon Wessing:
Measuring flow as concept for detecting game fun in the Pac-Man game. IEEE Congress on Evolutionary Computation 2008: 3448-3455 - [c29]Nicola Beume, Tobias Hein, Boris Naujoks, Georg Neugebauer, Nico Piatkowski, Mike Preuss, Raphael Stür, Andreas Thom:
To model or not to model: Controlling Pac-Man ghosts without incorporating global knowledge. IEEE Congress on Evolutionary Computation 2008: 3464-3471 - [c28]Nicola Beume, Tobias Hein, Boris Naujoks, Nico Piatkowski, Mike Preuss, Simon Wessing:
Intelligent anti-grouping in real-time strategy games. CIG 2008: 63-70 - [c27]Holger Danielsiek, Raphael Stür, Andreas Thom, Nicola Beume, Boris Naujoks, Mike Preuss:
Intelligent moving of groups in real-time strategy games. CIG 2008: 71-78 - [c26]Jens Jägersküpper, Mike Preuss:
Aiming for a theoretically tractable CSA variant by means of empirical investigations. GECCO 2008: 503-510 - [c25]Thomas Bartz-Beielstein, Mike Preuss:
Experimental research in evolutionary computation. GECCO (Companion) 2008: 2517-2534 - [c24]Claude Bouvy, Christoph Kausch, Mike Preuss, Frank Henrich:
On the Potential of Multi-objective Optimization in the Design of Sustainable Energy Systems. MCDM 2008: 3-12 - [c23]Mike Preuss, Christoph Kausch, Claude Bouvy, Frank Henrich:
Decision Space Diversity Can Be Essential for Solving Multiobjective Real-World Problems. MCDM 2008: 367-377 - [c22]Catalin Stoean, Mike Preuss, Ruxandra Stoean, Dumitru Dumitrescu:
EA-Powered Basin Number Estimation by Means of Preservation and Exploration. PPSN 2008: 569-578 - [c21]Heike Trautmann, Uwe Ligges, Jörn Mehnen, Mike Preuss:
A Convergence Criterion for Multiobjective Evolutionary Algorithms Based on Systematic Statistical Testing. PPSN 2008: 825-836 - [c20]Jens Jägersküpper, Mike Preuss:
Empirical Investigation of Simplified Step-Size Control in Metaheuristics with a View to Theory. WEA 2008: 263-274 - 2007
- [c19]Ruxandra Stoean, Mike Preuss, Catalin Stoean, Dumitru Dumitrescu:
Concerning the potential of evolutionary support vector machines. IEEE Congress on Evolutionary Computation 2007: 1436-1443 - [c18]Mike Preuss, Günter Rudolph, Feelly Tumakaka:
Solving multimodal problems via multiobjective techniques with Application to phase equilibrium detection. IEEE Congress on Evolutionary Computation 2007: 2703-2710 - [c17]Günter Rudolph, Boris Naujoks, Mike Preuss:
Capabilities of EMOA to Detect and Preserve Equivalent Pareto Subsets. EMO 2007: 36-50 - [c16]Catalin Stoean, Mike Preuss, Ruxandra Stoean, Dumitru Dumitrescu:
Disburdening the species conservation evolutionary algorithm of arguing with radii. GECCO 2007: 1420-1427 - [c15]Thomas Bartz-Beielstein, Mike Preuss:
Experimental research in evolutionary computation. GECCO (Companion) 2007: 3001-3020 - [c14]Markus Chimani, Maria Kandyba, Mike Preuss:
Hybrid Numerical Optimization for Combinatorial Network Problems. Hybrid Metaheuristics 2007: 185-200 - 2006
- [c13]Mario Giacobini, Mike Preuss, Marco Tomassini:
Effects of Scale-Free and Small-World Topologies on Binary Coded Self-adaptive CEA. EvoCOP 2006: 86-98 - [c12]Thomas Bartz-Beielstein, Mike Preuss, Günter Rudolph:
Investigation of One-Go Evolution Strategy/Quasi-Newton Hybridizations. Hybrid Metaheuristics 2006: 178-191 - [c11]Mike Preuss, Boris Naujoks, Günter Rudolph:
Pareto Set and EMOA Behavior for Simple Multimodal Multiobjective Functions. PPSN 2006: 513-522 - [c10]Catalin Stoean, Mike Preuss, Dumitru Dumitrescu, Ruxandra Stoean:
Cooperative Evolution of Rules for Classification. SYNASC 2006: 317-322 - [c9]Ruxandra Stoean, Dumitru Dumitrescu, Mike Preuss, Catalin Stoean:
Evolutionary Support Vector Regression Machines. SYNASC 2006: 330-335 - 2005
- [c8]Thomas Bartz-Beielstein, Christian Lasarczyk, Mike Preuss:
Sequential parameter optimization. Congress on Evolutionary Computation 2005: 773-780 - [c7]Catalin Stoean, Mike Preuss, Ruxandra Gorunescu, Dumitru Dumitrescu:
Elitist generational genetic chromodynamics - a new radii-based evolutionary algorithm for multimodal optimization. Congress on Evolutionary Computation 2005: 1839-1846 - [c6]Mike Preuss, Lutz Schönemann, Michael Emmerich:
Counteracting genetic drift and disruptive recombination in (µ, +lambda)-EA on multimodal fitness landscapes. GECCO 2005: 865-872 - 2004
- [c5]Mike Preuss, Christian Lasarczyk:
On the Importance of Information Speed in Structured Populations. PPSN 2004: 91-100 - 2002
- [c4]Márk Jelasity, Mike Preuß, Maarten van Steen, Ben Paechter:
Maintaining Connectivity in a Scalable and Robust Distributed Environment. CCGRID 2002: 389-394 - [c3]Márk Jelasity, Mike Preuß:
On Obtaining Global Information in a Peer-to-Peer Fully Distributed Environment (Research Note). Euro-Par 2002: 573-577 - [c2]Márk Jelasity, Mike Preuß, A. E. Eiben:
Operator Learning for a Problem Class in a Distributed Peer-to-Peer Environment. PPSN 2002: 172-183 - [c1]Maribel García Arenas, Pierre Collet, A. E. Eiben, Márk Jelasity, Juan Julián Merelo Guervós, Ben Paechter, Mike Preuß, Marc Schoenauer:
A Framework for Distributed Evolutionary Algorithms. PPSN 2002: 665-675
Parts in Books or Collections
- 2021
- [p12]Mike Preuss, Michael Epitropakis, Xiaodong Li, Jonathan E. Fieldsend:
Multimodal Optimization: Formulation, Heuristics, and a Decade of Advances. Metaheuristics for Finding Multiple Solutions 2021: 1-26 - 2016
- [p11]Simon Wessing, Günter Rudolph, Mike Preuss:
Assessing Basin Identification Methods for Locating Multiple Optima. Advances in Stochastic and Deterministic Global Optimization 2016: 53-70 - 2015
- [p10]Mike Preuss, Simon Wessing, Günter Rudolph, Gabriele Sadowski:
Solving Phase Equilibrium Problems by Means of Avoidance-Based Multiobjectivization. Handbook of Computational Intelligence 2015: 1159-1171 - 2014
- [p9]Thomas Bartz-Beielstein, Mike Preuss:
Experimental Analysis of Optimization Algorithms: Tuning and Beyond. Theory and Principled Methods for the Design of Metaheuristics 2014: 205-245 - 2013
- [p8]Julian Togelius, Alex J. Champandard, Pier Luca Lanzi, Michael Mateas, Ana Paiva, Mike Preuss, Kenneth O. Stanley:
Procedural Content Generation: Goals, Challenges and Actionable Steps. Artificial and Computational Intelligence in Games 2013: 61-75 - 2012
- [p7]Markus Kemmerling, Niels Ackermann, Mike Preuss:
Making Diplomacy Bots Individual. Believable Bots 2012: 265-288 - 2010
- [p6]Thomas Bartz-Beielstein, Marco Chiarandini, Luís Paquete, Mike Preuss:
Introduction. Experimental Methods for the Analysis of Optimization Algorithms 2010: 1-13 - [p5]Thomas Bartz-Beielstein, Mike Preuss:
The Future of Experimental Research. Experimental Methods for the Analysis of Optimization Algorithms 2010: 17-49 - [p4]Thomas Bartz-Beielstein, Christian Lasarczyk, Mike Preuss:
The Sequential Parameter Optimization Toolbox. Experimental Methods for the Analysis of Optimization Algorithms 2010: 337-362 - 2009
- [p3]Ruxandra Stoean, Mike Preuss, Catalin Stoean, Elia El-Darzi, D. Dumitrescu:
An Evolutionary Approximation for the Coefficients of Decision Functions within a Support Vector Machine Learning Strategy. Foundations of Computational Intelligence (1) 2009: 83-114 - [p2]Ruxandra Stoean, Mike Preuss, Catalin Stoean, Elia El-Darzi, D. Dumitrescu:
An Evolutionary Approximation for the Coefficients of Decision Functions within a Support Vector Machine Learning Strategy. Foundations of Computational Intelligence (3) 2009: 315-346 - 2007
- [p1]Mike Preuss, Thomas Bartz-Beielstein:
Sequential Parameter Optimization Applied to Self-Adaptation for Binary-Coded Evolutionary Algorithms. Parameter Setting in Evolutionary Algorithms 2007: 91-119
Editorship
- 2021
- [e11]Mike Preuss, Michael G. Epitropakis, Xiaodong Li, Jonathan E. Fieldsend:
Metaheuristics for Finding Multiple Solutions. Natural Computing Series, Springer 2021, ISBN 978-3-030-79552-8 [contents] - 2020
- [e10]Christian Grimme, Mike Preuss, Frank W. Takes, Annie Waldherr:
Disinformation in Open Online Media - First Multidisciplinary International Symposium, MISDOOM 2019, Hamburg, Germany, February 27 - March 1, 2019, Revised Selected Papers. Lecture Notes in Computer Science 12021, Springer 2020, ISBN 978-3-030-39626-8 [contents] - [e9]Max J. van Duijn, Mike Preuss, Viktoria Spaiser, Frank W. Takes, Suzan Verberne:
Disinformation in Open Online Media - Second Multidisciplinary International Symposium, MISDOOM 2020, Leiden, The Netherlands, October 26-27, 2020, Proceedings. Lecture Notes in Computer Science 12259, Springer 2020, ISBN 978-3-030-61840-7 [contents] - [e8]Thomas Bäck, Mike Preuss, André H. Deutz, Hao Wang, Carola Doerr, Michael T. M. Emmerich, Heike Trautmann:
Parallel Problem Solving from Nature - PPSN XVI - 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part I. Lecture Notes in Computer Science 12269, Springer 2020, ISBN 978-3-030-58111-4 [contents] - [e7]Thomas Bäck, Mike Preuss, André H. Deutz, Hao Wang, Carola Doerr, Michael T. M. Emmerich, Heike Trautmann:
Parallel Problem Solving from Nature - PPSN XVI - 16th International Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020, Proceedings, Part II. Lecture Notes in Computer Science 12270, Springer 2020, ISBN 978-3-030-58114-5 [contents] - 2013
- [e6]Simon M. Lucas, Michael Mateas, Mike Preuss, Pieter Spronck, Julian Togelius:
Artificial and Computational Intelligence in Games. Dagstuhl Follow-Ups 6, Schloss Dagstuhl - Leibniz-Zentrum für Informatik 2013, ISBN 978-3-939897-62-0 [contents] - 2012
- [e5]Cecilia Di Chio, Alexandros Agapitos, Stefano Cagnoni, Carlos Cotta, Francisco Fernández de Vega, Gianni A. Di Caro, Rolf Drechsler, Anikó Ekárt, Anna Isabel Esparcia-Alcázar, Muddassar Farooq, William B. Langdon, Juan Julián Merelo Guervós, Mike Preuss, Hendrik Richter, Sara Silva, Anabela Simões, Giovanni Squillero, Ernesto Tarantino, Andrea Tettamanzi, Julian Togelius, Neil Urquhart, Sima Uyar, Georgios N. Yannakakis:
Applications of Evolutionary Computation - EvoApplications 2012: EvoCOMNET, EvoCOMPLEX, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoNUM, EvoPAR, EvoRISK, EvoSTIM, and EvoSTOC, Málaga, Spain, April 11-13, 2012, Proceedings. Lecture Notes in Computer Science 7248, Springer 2012, ISBN 978-3-642-29177-7 [contents] - 2011
- [e4]Cecilia Di Chio, Stefano Cagnoni, Carlos Cotta, Marc Ebner, Anikó Ekárt, Anna Esparcia-Alcázar, Juan Julián Merelo Guervós, Ferrante Neri, Mike Preuss, Hendrik Richter, Julian Togelius, Georgios N. Yannakakis:
Applications of Evolutionary Computation - EvoApplications 2011: EvoCOMPLEX, EvoGAMES, EvoIASP, EvoINTELLIGENCE, EvoNUM, and EvoSTOC, Torino, Italy, April 27-29, 2011, Proceedings, Part I. Lecture Notes in Computer Science 6624, Springer 2011, ISBN 978-3-642-20524-8 [contents] - 2010
- [e3]Thomas Bartz-Beielstein, Marco Chiarandini, Luís Paquete, Mike Preuss:
Experimental Methods for the Analysis of Optimization Algorithms. Springer 2010, ISBN 978-3-642-02537-2 [contents] - [e2]Cecilia Di Chio, Stefano Cagnoni, Carlos Cotta, Marc Ebner, Anikó Ekárt, Anna Esparcia-Alcázar, Chi Keong Goh, Juan Julián Merelo Guervós, Ferrante Neri, Mike Preuss, Julian Togelius, Georgios N. Yannakakis:
Applications of Evolutionary Computation, EvoApplicatons 2010: EvoCOMPLEX, EvoGAMES, EvoIASP, EvoINTELLIGENCE, EvoNUM, and EvoSTOC, Istanbul, Turkey, April 7-9, 2010, Proceedings, Part I. Lecture Notes in Computer Science 6024, Springer 2010, ISBN 978-3-642-12238-5 [contents] - 2009
- [e1]Mario Giacobini, Anthony Brabazon, Stefano Cagnoni, Gianni A. Di Caro, Anikó Ekárt, Anna Esparcia-Alcázar, Muddassar Farooq, Andreas Fink, Penousal Machado, Jon McCormack, Michael O'Neill, Ferrante Neri, Mike Preuss, Franz Rothlauf, Ernesto Tarantino, Shengxiang Yang:
Applications of Evolutionary Computing, EvoWorkshops 2009: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG, Tübingen, Germany, April 15-17, 2009. Proceedings. Lecture Notes in Computer Science 5484, Springer 2009, ISBN 978-3-642-01128-3 [contents]
Reference Works
- 2019
- [r2]David Churchill, Mike Preuss, Florian Richoux, Gabriel Synnaeve, Alberto Uriarte, Santiago Ontañón, Michal Certický:
StarCraft Bots and Competitions. Encyclopedia of Computer Graphics and Games 2019 - [r1]Santiago Ontañón, Gabriel Synnaeve, Alberto Uriarte, Florian Richoux, David Churchill, Mike Preuss:
RTS AI Problems and Techniques. Encyclopedia of Computer Graphics and Games 2019
Informal and Other Publications
- 2023
- [i36]Zhao Yang, Thomas M. Moerland, Mike Preuss, Aske Plaat:
Two-Memory Reinforcement Learning. CoRR abs/2304.10098 (2023) - [i35]Paula Torren-Peraire, Alan Kai Hassen, Samuel Genheden, Jonas Verhoeven, Djork-Arné Clevert, Mike Preuss, Igor V. Tetko:
Models Matter: The Impact of Single-Step Retrosynthesis on Synthesis Planning. CoRR abs/2308.05522 (2023) - [i34]Arthur van der Staaij, Jelmer Prins, Vincent L. Prins, Julian Poelsma, Thera Smit, Matthias Müller-Brockhausen, Mike Preuss:
Believable Minecraft Settlements by Means of Decentralised Iterative Planning. CoRR abs/2309.10871 (2023) - [i33]Marco Pleines, Matthias Pallasch, Frank Zimmer, Mike Preuss:
Memory Gym: Partially Observable Challenges to Memory-Based Agents in Endless Episodes. CoRR abs/2309.17207 (2023) - 2022
- [i32]Matthias Müller-Brockhausen, Aske Plaat, Mike Preuss:
Reliable validation of Reinforcement Learning Benchmarks. CoRR abs/2203.01075 (2022) - [i31]Zhao Yang, Thomas M. Moerland, Mike Preuss, Aske Plaat:
When to Go, and When to Explore: The Benefit of Post-Exploration in Intrinsic Motivation. CoRR abs/2203.16311 (2022) - [i30]Marco Pleines, Konstantin Ramthun, Yannik Wegener, Hendrik Meyer, Matthias Pallasch, Sebastian Prior, Jannik Drögemüller, Leon Büttinghaus, Thilo Röthemeyer, Alexander Kaschwig, Oliver Chmurzynski, Frederik Rohkrähmer, Roman Kalkreuth, Frank Zimmer, Mike Preuss:
On the Verge of Solving Rocket League using Deep Reinforcement Learning and Sim-to-sim Transfer. CoRR abs/2205.05061 (2022) - [i29]Marco Pleines, Matthias Pallasch, Frank Zimmer, Mike Preuss:
Generalization, Mayhems and Limits in Recurrent Proximal Policy Optimization. CoRR abs/2205.11104 (2022) - [i28]Zhao Yang, Thomas M. Moerland, Mike Preuss, Aske Plaat:
Continuous Episodic Control. CoRR abs/2211.15183 (2022) - [i27]Zhao Yang, Thomas M. Moerland, Mike Preuss, Aske Plaat:
First Go, then Post-Explore: the Benefits of Post-Exploration in Intrinsic Motivation. CoRR abs/2212.03251 (2022) - [i26]Alan Kai Hassen, Paula Torren-Peraire, Samuel Genheden, Jonas Verhoeven, Mike Preuss, Igor V. Tetko:
Mind the Retrosynthesis Gap: Bridging the divide between Single-step and Multi-step Retrosynthesis Prediction. CoRR abs/2212.11809 (2022) - 2021
- [i25]Alexander Hagg, Mike Preuss, Alexander Asteroth, Thomas Bäck:
An Analysis of Phenotypic Diversity in Multi-Solution Optimization. CoRR abs/2105.04252 (2021) - [i24]Hui Wang, Mike Preuss, Aske Plaat:
Adaptive Warm-Start MCTS in AlphaZero-like Deep Reinforcement Learning. CoRR abs/2105.06136 (2021) - [i23]Zhao Yang, Mike Preuss, Aske Plaat:
Transfer Learning and Curriculum Learning in Sokoban. CoRR abs/2105.11702 (2021) - [i22]Matthias Müller-Brockhausen, Mike Preuss, Aske Plaat:
Procedural Content Generation: Better Benchmarks for Transfer Reinforcement Learning. CoRR abs/2105.14780 (2021) - [i21]Aske Plaat, Walter A. Kosters, Mike Preuss:
High-Accuracy Model-Based Reinforcement Learning, a Survey. CoRR abs/2107.08241 (2021) - [i20]Christoph Salge, Claus Aranha, Adrian Brightmoore, Sean Butler, Rodrigo Canaan, Michael Cook, Michael Cerny Green, Hagen Fischer, Christian Guckelsberger, Jupiter Hadley, Jean-Baptiste Hervé, Mark Richard Johnson, Quinn Kybartas, David Mason, Mike Preuss, Tristan Smith, Ruck Thawonmas, Julian Togelius:
Impressions of the GDMC AI Settlement Generation Challenge in Minecraft. CoRR abs/2108.02955 (2021) - [i19]Zhao Yang, Mike Preuss, Aske Plaat:
Potential-based Reward Shaping in Sokoban. CoRR abs/2109.05022 (2021) - 2020
- [i18]Sebastian Risi, Mike Preuss:
From Chess and Atari to StarCraft and Beyond: How Game AI is Driving the World of AI. CoRR abs/2002.10433 (2020) - [i17]Hui Wang, Michael Emmerich, Mike Preuss, Aske Plaat:
Analysis of Hyper-Parameters for Small Games: Iterations or Epochs in Self-Play? CoRR abs/2003.05988 (2020) - [i16]Lena Clever, Dennis Assenmacher, Kilian Müller, Moritz Vinzent Seiler, Dennis M. Riehle, Mike Preuss, Christian Grimme:
FakeYou! - A Gamified Approach for Building and Evaluating Resilience Against Fake News. CoRR abs/2003.07595 (2020) - [i15]Matthias Müller-Brockhausen, Mike Preuss, Aske Plaat:
A New Challenge: Approaching Tetris Link with AI. CoRR abs/2004.00377 (2020) - [i14]Marco Pleines, Jenia Jitsev, Mike Preuss, Frank Zimmer:
Obstacle Tower Without Human Demonstrations: How Far a Deep Feed-Forward Network Goes with Reinforcement Learning. CoRR abs/2004.00567 (2020) - [i13]Hui Wang, Mike Preuss, Aske Plaat:
Warm-Start AlphaZero Self-Play Search Enhancements. CoRR abs/2004.12357 (2020) - [i12]Jialin Liu, Antoine Moreau, Mike Preuss, Baptiste Rozière, Jérémy Rapin, Fabien Teytaud, Olivier Teytaud:
Versatile Black-Box Optimization. CoRR abs/2004.14014 (2020) - [i11]Hui Wang, Mike Preuss, Michael Emmerich, Aske Plaat:
Tackling Morpion Solitaire with AlphaZero-likeRanked Reward Reinforcement Learning. CoRR abs/2006.07970 (2020) - [i10]Aske Plaat, Walter A. Kosters, Mike Preuss:
Model-Based Deep Reinforcement Learning for High-Dimensional Problems, a Survey. CoRR abs/2008.05598 (2020) - [i9]Christoph Salge, Emily Short, Mike Preuss, Spyridon Samothrakis, Pieter Spronck:
Applications of Artificial Intelligence in Live Action Role-Playing Games (LARP). CoRR abs/2008.11003 (2020) - 2019
- [i8]Hui Wang, Michael Emmerich, Mike Preuss, Aske Plaat:
Hyper-Parameter Sweep on AlphaZero General. CoRR abs/1903.08129 (2019) - 2017
- [i7]Marwin H. S. Segler, Mike Preuß, Mark P. Waller:
Towards "AlphaChem": Chemical Synthesis Planning with Tree Search and Deep Neural Network Policies. CoRR abs/1702.00020 (2017) - [i6]Simon Wessing, Mike Preuss:
The True Destination of EGO is Multi-local Optimization. CoRR abs/1704.05724 (2017) - [i5]Christian Grimme, Mike Preuss, Lena Adam, Heike Trautmann:
Social Bots: Human-Like by Means of Human Control? CoRR abs/1706.07624 (2017) - [i4]Marwin H. S. Segler, Mike Preuss, Mark P. Waller:
Learning to Plan Chemical Syntheses. CoRR abs/1708.04202 (2017) - [i3]Pieter Spronck, Elisabeth André, Michael Cook, Mike Preuß:
Artificial and Computational Intelligence in Games: AI-Driven Game Design (Dagstuhl Seminar 17471). Dagstuhl Reports 7(11): 86-129 (2017) - 2015
- [i2]Simon M. Lucas, Michael Mateas, Mike Preuss, Pieter Spronck, Julian Togelius:
Artificial and Computational Intelligence in Games: Integration (Dagstuhl Seminar 15051). Dagstuhl Reports 5(1): 207-242 (2015) - 2012
- [i1]Simon M. Lucas, Michael Mateas, Mike Preuss, Pieter Spronck, Julian Togelius:
Artificial and Computational Intelligence in Games (Dagstuhl Seminar 12191). Dagstuhl Reports 2(5): 43-70 (2012)
Coauthor Index
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