| Multi-agent positioning mechanism in the dynamic environment H Akiyama, I Noda RoboCup 2007: Robot Soccer World Cup XI 11, 377-384, 2008 | 97 | 2008 |
| Multirobot exploration for search and rescue missions: A report on map building in RoboCupRescue 2009 K Nagatani, Y Okada, N Tokunaga, S Kiribayashi, K Yoshida, K Ohno, ... Journal of Field Robotics 28 (3), 373-387, 2011 | 92 | 2011 |
| Helios base: An open source package for the robocup soccer 2d simulation H Akiyama, T Nakashima RoboCup 2013: Robot World Cup XVII 17, 528-535, 2014 | 91 | 2014 |
| Helios2013 team description paper H Akiyama, T Nakashima, K Yamashita, S Mifune RoboCup 2019 Symposium and Competitions, Sydney, Australia, 2019 | 54 | 2019 |
| Helios2009 team description H Akiyama, H Shimora, I Noda 12th RoboCup International Symposium.(July 2008)(CD Supplement), 25, 2009 | 39 | 2009 |
| Online cooperative behavior planning using a tree search method in the robocup soccer simulation H Akiyama, S Aramaki, T Nakashima 2012 Fourth International Conference on Intelligent Networking and …, 2012 | 33 | 2012 |
| Helios2018: Robocup 2018 soccer simulation 2D league champion H Akiyama, T Nakashima, T Fukushima, J Zhong, Y Suzuki, A Ohori RoboCup 2018: Robot World Cup XXII 22, 450-461, 2019 | 29 | 2019 |
| Field experiment on multiple mobile robots conducted in an underground mall T Yoshida, K Nagatani, E Koyanagi, Y Hada, K Ohno, S Maeyama, ... Field and Service Robotics: Results of the 7th International Conference, 365-375, 2010 | 24 | 2010 |
| Learning evaluation function for decision making of soccer agents using learning to rank H Akiyama, M Tsuji, S Aramaki 2016 Joint 8th International Conference on Soft Computing and Intelligent …, 2016 | 14 | 2016 |
| Similarity analysis of action trajectories based on kick distributions T Fukushima, T Nakashima, H Akiyama Robot World Cup, 58-70, 2019 | 13 | 2019 |
| Mimicking an expert team through the learning of evaluation functions from action sequences T Fukushima, T Nakashima, H Akiyama RoboCup 2018: Robot World Cup XXII 22, 170-180, 2019 | 13 | 2019 |
| Online opponent formation identification based on position information T Fukushima, T Nakashima, H Akiyama RoboCup 2017: Robot World Cup XXI 11, 241-251, 2018 | 12 | 2018 |
| On the progress of soccer simulation leagues H Akiyama, K Dorer, N Lau RoboCup 2014: Robot World Cup XVIII 18, 599-610, 2015 | 12 | 2015 |
| Helios 2021: team description paper M Yamaguchi, R Kuga, H Omori, T Fukushima, T Nakashima, H Akiyama RoboCup 2021 Symposium and Competitions, Worldwide, 2021 | 10 | 2021 |
| Training of Agent Positioning Using Human’s Instruction H Akiyama, D Katagami, K Nitta Journal of Advanced Computational Intelligence and Intelligent Informatics …, 2007 | 10 | 2007 |
| Learning Evaluation Function for RoboCup Soccer Simulation using Humans' Choice H Akiyama, M Fukuyado, T Gochou, S Aramaki 2018 Joint 10th International Conference on Soft Computing and Intelligent …, 2018 | 9 | 2018 |
| Helios2018: Team description paper T Nakashima, H Akiyama, Y Suzuki, A Ohori, T Fukushima RoboCup 2018 Symposium and Competitions: Team Description Papers, Montreal …, 2018 | 8 | 2018 |
| Game-watching should be more entertaining: real-time application of field-situation prediction to a soccer monitor Y Suzuki, T Fukushima, L Thibout, T Nakashima, H Akiyama RoboCup 2019: Robot World Cup XXIII 23, 439-447, 2019 | 7 | 2019 |
| Selecting the best player formation for corner-kick situations based on Bayes’ estimation J Henrio, T Henn, T Nakashima, H Akiyama RoboCup 2016: Robot World Cup XX 20, 428-439, 2017 | 6 | 2017 |
| Evaluation-function modeling with multi-layered perceptron for RoboCup soccer 2D simulation T Fukushima, T Nakashima, H Akiyama Artificial Life and Robotics 25, 440-445, 2020 | 5 | 2020 |
Tomoharu NakashimaOsaka Prefecture UniversityVerified email at kis.osakafu-u.ac.jp
