| Adapting everyday manipulation skills to varied scenarios P Gajewski, P Ferreira, G Bartels, C Wang, F Guerin, B Indurkhya, ... 2019 International Conference on Robotics and Automation (ICRA), 1345-1351, 2019 | 26 | 2019 |
| VM reservation plan adaptation using machine learning in cloud computing B Sniezynski, P Nawrocki, M Wilk, M Jarzab, K Zielinski Journal of Grid Computing 17, 797-812, 2019 | 24 | 2019 |
| A comparison of native and cross-platform frameworks for mobile applications P Nawrocki, K Wrona, M Marczak, B Sniezynski Computer 54 (3), 18-27, 2021 | 23 | 2021 |
| Adaptive service management in mobile cloud computing by means of supervised and reinforcement learning P Nawrocki, B Sniezynski Journal of Network and Systems Management 26 (1), 1-22, 2018 | 22 | 2018 |
| Adaptable mobile cloud computing environment with code transfer based on machine learning P Nawrocki, B Sniezynski, H Slojewski Pervasive and Mobile Computing 57, 49-63, 2019 | 21 | 2019 |
| The use of LPR (logic of plausible reasoning) to obtain information on innovative casting technologies S Kluska-Nawarecka, B Śnieżyński, W Parada, M Lustofin, ... Archives of Civil and Mechanical Engineering 14 (1), 25-31, 2014 | 21 | 2014 |
| Learning agent for a service-oriented context-aware recommender system in heterogeneous environment P Nawrocki, B Sniezynski Computing and Informatics 35 (5), 1005-1026, 2016 | 18 | 2016 |
| Neural network modelling studies of steam oxidised kinetic behaviour of advanced steels and Ni-based alloys at 800° C for 3000 h T Dudziak, P Gajewski, B Śnieżyński, V Deodeshmukh, M Witkowska, ... Corrosion Science 133, 94-111, 2018 | 14 | 2018 |
| Autonomous context-based service optimization in mobile cloud computing P Nawrocki, B Sniezynski Journal of Grid computing 15, 343-356, 2017 | 14 | 2017 |
| Agent-based adaptation system for service-oriented architectures using supervised learning B Śnieżyński Procedia Computer Science 29, 1057-1067, 2014 | 13 | 2014 |
| Agent strategy generation by rule induction B Sniezynski Computing and Informatics 32, 1055-1078, 2013 | 13 | 2013 |
| Proof searching algorithm for the logic of plausible reasoning B Śnieżyński Intelligent Information Processing and Web Mining: Proceedings of the …, 2003 | 13 | 2003 |
| A strategy learning model for autonomous agents based on classification B SNIEZYNSKI Int. J. Appl. Math. Comput. Sci 25 (3), 471-482, 2015 | 12 | 2015 |
| Combining rule induction and reinforcement learning: An agent-based vehicle routing B Śniezyński, W Wójcik, JD Gehrke, J Wojtusiak 2010 Ninth International Conference on Machine Learning and Applications …, 2010 | 12 | 2010 |
| Knowledge visualization using optimized general logic diagrams B Śnieżyński, R Szymacha, RS Michalski Intelligent Information Processing and Web Mining: Proceedings of the …, 2005 | 12 | 2005 |
| Watch: Wasserstein change point detection for high-dimensional time series data K Faber, R Corizzo, B Sniezynski, M Baron, N Japkowicz 2021 IEEE International Conference on Big Data (Big Data), 4450-4459, 2021 | 11 | 2021 |
| Adaptive context-aware energy optimization for services on mobile devices with use of machine learning P Nawrocki, B Sniezynski Wireless Personal Communications 115 (3), 1839-1867, 2020 | 11 | 2020 |
| Comparison of strategy learning methods in farmer–pest problem for various complexity environments without delays B Śnieżyński, J Dajda Journal of Computational Science 4 (3), 144-151, 2013 | 11 | 2013 |
| Converting a naive bayes model into a set of rules B Śnieżyński Intelligent Information Processing and Web Mining: Proceedings of the …, 2006 | 11 | 2006 |
| Probabilistic label algebra for the logic of plausible reasoning B Śnieżyński Intelligent Information Systems 2002: Proceedings of the IIS’2002 Symposium …, 2002 | 11 | 2002 |
Piotr NawrockiAGHVerified email at agh.edu.pl
