| Evolving mario levels in the latent space of a deep convolutional generative adversarial network V Volz, J Schrum, J Liu, SM Lucas, A Smith, S Risi Proceedings of the genetic and evolutionary computation conference, 221-228, 2018 | 275 | 2018 |
| UT^2: Human-like behavior via neuroevolution of combat behavior and replay of human traces J Schrum, IV Karpov, R Miikkulainen 2011 IEEE Conference on Computational Intelligence and Games (CIG'11), 329-336, 2011 | 77 | 2011 |
| Evolving multimodal behavior with modular neural networks in Ms. Pac-Man J Schrum, R Miikkulainen Proceedings of the 2014 annual conference on genetic and evolutionary …, 2014 | 63 | 2014 |
| Interactive evolution and exploration within latent level-design space of generative adversarial networks J Schrum, J Gutierrez, V Volz, J Liu, S Lucas, S Risi Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 148-156, 2020 | 60 | 2020 |
| Believable bot navigation via playback of human traces IV Karpov, J Schrum, R Miikkulainen Believable Bots: Can Computers Play Like People?, 151-170, 2012 | 41 | 2012 |
| Human-like combat behaviour via multiobjective neuroevolution J Schrum, IV Karpov, R Miikkulainen Believable Bots: Can Computers Play Like People?, 119-150, 2012 | 40 | 2012 |
| Discovering multimodal behavior in Ms. Pac-Man through evolution of modular neural networks J Schrum, R Miikkulainen IEEE transactions on computational intelligence and AI in games 8 (1), 67-81, 2015 | 39 | 2015 |
| Constructing complex NPC behavior via multi-objective neuroevolution J Schrum, R Miikkulainen Proceedings of the AAAI Conference on Artificial Intelligence and …, 2008 | 36 | 2008 |
| Generative adversarial network rooms in generative graph grammar dungeons for the legend of zelda J Gutierrez, J Schrum 2020 IEEE Congress on Evolutionary Computation (CEC), 1-8, 2020 | 35 | 2020 |
| Cppn2gan: Combining compositional pattern producing networks and gans for large-scale pattern generation J Schrum, V Volz, S Risi Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 139-147, 2020 | 35 | 2020 |
| Evolving multimodal networks for multitask games J Schrum, R Miikkulainen IEEE Transactions on Computational Intelligence and AI in Games 4 (2), 94-111, 2012 | 35 | 2012 |
| Evolving multi-modal behavior in NPCs J Schrum, R Miikkulainen 2009 IEEE Symposium on Computational Intelligence and Games, 325-332, 2009 | 28 | 2009 |
| Evolving agent behavior in multiobjective domains using fitness-based shaping J Schrum, R Miikkulainen Proceedings of the 12th annual conference on Genetic and evolutionary …, 2010 | 25 | 2010 |
| Illuminating the space of beatable lode runner levels produced by various generative adversarial networks K Steckel, J Schrum Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2021 | 21 | 2021 |
| Divide and conquer: neuroevolution for multiclass classification T McDonnell, S Andoni, E Bonab, S Cheng, JH Choi, J Goode, K Moore, ... Proceedings of the genetic and evolutionary computation conference, 474-481, 2018 | 21 | 2018 |
| Evolving indirectly encoded convolutional neural networks to play tetris with low-level features J Schrum Proceedings of the genetic and evolutionary computation conference, 205-212, 2018 | 17 | 2018 |
| Comparing direct and indirect encodings using both raw and hand-designed features in tetris LE Gillespie, GR Gonzalez, J Schrum Proceedings of the Genetic and Evolutionary Computation Conference, 179-186, 2017 | 15 | 2017 |
| Solving Multiple Isolated, Interleaved, and Blended Tasks through Modular Neuroevolution J Schrum, R Miikkulainen Evolutionary computation 24 (3), 459-490, 2016 | 12 | 2016 |
| Using multiple generative adversarial networks to build better-connected levels for mega man B Capps, J Schrum Proceedings of the Genetic and Evolutionary Computation Conference, 66-74, 2021 | 9 | 2021 |
| Desirable behaviors for companion bots in first-person shooters A Friedman, J Schrum 2019 IEEE Conference on Games (CoG), 1-8, 2019 | 8 | 2019 |
Risto MiikkulainenProfessor of Computer Science, the University of Texas at Austin在 cs.utexas.edu 的电子邮件经过验证
