| Identifying useful subgoals in reinforcement learning by local graph partitioning Ö Şimşek, AP Wolfe, AG Barto Proceedings of the 22nd international conference on Machine learning, 816-823, 2005 | 339 | 2005 |
| Using relative novelty to identify useful temporal abstractions in reinforcement learning Ö Şimşek, AG Barto Proceedings of the twenty-first international conference on Machine learning, 95, 2004 | 292 | 2004 |
| Skill characterization based on betweenness Ö Şimşek, A Barto Advances in neural information processing systems 21, 2008 | 207 | 2008 |
| Using relational knowledge discovery to prevent securities fraud J Neville, Ö Şimşek, D Jensen, J Komoroske, K Palmer, H Goldberg Proceedings of the eleventh ACM SIGKDD international conference on Knowledge …, 2005 | 162 | 2005 |
| An intrinsic reward mechanism for efficient exploration Ö Şimşek, AG Barto Proceedings of the 23rd international conference on Machine learning, 833-840, 2006 | 146 | 2006 |
| Navigating networks by using homophily and degree Ö Şimşek, D Jensen Proceedings of the National Academy of Sciences 105 (35), 12758-12762, 2008 | 143 | 2008 |
| Credit growth, the yield curve and financial crisis prediction: Evidence from a machine learning approach K Bluwstein, M Buckmann, A Joseph, S Kapadia, Ö Şimşek Journal of International Economics 145, 103773, 2023 | 109 | 2023 |
| Classification in the wild: The science and art of transparent decision making KV Katsikopoulos, Ö Şimşek, M Buckmann, G Gigerenzer MIT Press, 2021 | 83* | 2021 |
| Linear decision rule as aspiration for simple decision heuristics Ö Şimşek Advances in neural information processing systems 26, 2013 | 70 | 2013 |
| Decentralized search in networks using homophily and degree disparity O Simsek, D Jensen IJCAI, 304-310, 2005 | 69 | 2005 |
| Intrinsic motivation for reinforcement learning systems AG Barto, O Simsek Proceedings of the thirteenth yale workshop on adaptive and learning systems …, 2005 | 68 | 2005 |
| On-road versus simulator data in driver model development driver performance model experience AC Bittner Jr, O Simsek, WH Levison, JL Campbell Transportation research record 1803 (1), 38-44, 2002 | 53 | 2002 |
| Simple regression models JM Lichtenberg, Ö Şimşek Imperfect decision makers: Admitting real-world rationality, 13-25, 2017 | 45 | 2017 |
| Secondary-task measures of driver workload BH Kantowitz, O Simsek Stress, workload, and fatigue, 395-408, 2000 | 42 | 2000 |
| Learning from small samples: An analysis of simple decision heuristics Ö Şimşek, M Buckmann Advances in neural information processing systems 28, 2015 | 40 | 2015 |
| Transparent modeling of influenza incidence: Big data or a single data point from psychological theory? KV Katsikopoulos, Ö Şimşek, M Buckmann, G Gigerenzer International Journal of Forecasting 38 (2), 613-619, 2022 | 38 | 2022 |
| Behavioral building blocks for autonomous agents: description, identification, and learning O Simsek University of Massachusetts Amherst, 2008 | 35 | 2008 |
| Why most decisions are easy in tetris—and perhaps in other sequential decision problems, as well Ö Şimşek, S Algorta, A Kothiyal International Conference on Machine Learning, 1757-1765, 2016 | 34 | 2016 |
| Autocorrelation and relational learning: Challenges and opportunities J Neville, Ö Şimşek, D Jensen ICML 2004 Workshop on Statistical Relational Learning and its Connections to …, 2004 | 32 | 2004 |
| The game of Tetris in machine learning S Algorta, Ö Şimşek arXiv preprint arXiv:1905.01652, 2019 | 19 | 2019 |
Andrew BartoUniversity of Massachusetts Amherst在 cs.umass.edu 的电子邮件经过验证
