Yohei Hayamizu (PhD student)
Autonomous Intelligent Robotics Lab. Department of Computer Science, SUNY Binghamton.
Research Area:
Artificial Intelligence, Robotics, Reinforcement Learning, Dialog Navigation Systems
Contact:
yhayami1 "at" binghamton.edu
Proceedings
2023

  • Yohei Hayamizu, Zhou Yu, and Shiqi Zhang: Learning Joint Policies for Human-Robot Dialog and Co-Navigation, IEEE/RSJ International Conference on Intelligent Robots (IROS), 2023. (Paper)

  • Hiroki Shiraishi, Yohei Hayamizu, Tomonori Hashiyama: Fuzzy-UCS Revisited: Self-Adaptation of Rule Representations in Michigan-Style Learning Fuzzy-Classifier Systems, The Genetic and Evolutionary Computation Conference (GECCO), 2023. (Paper)

2022

  • Hiroki Shiraishi, Yohei Hayamizu (co-author), Hiroyuki Sato, Keiki Takadama: Beta Distribution-based XCS Classifier System, IEEE Congress on Evolutionary Computation (CEC), 2022. (Paper)

  • Hiroki Shiraishi, Yohei Hayamizu, Hiroyuki Sato, Keiki Takadama: Can the same rule representation change its matching area? enhancing representation in XCS for continuous space by probability distribution in multiple dimension, The Genetic and Evolutionary Computation Conference (GECCO), 2022. (Paper)

  • Hiroki Shiraishi, Yohei Hayamizu, Hiroyuki Sato, Keiki Takadama: Absumption based on overgenerality and condition-clustering based specialization for XCS with continuous-valued inputs, The Genetic and Evolutionary Computation Conference (GECCO), 2022. (Paper Best Paper Award)

  • Hiroki Shiraishi, Yohei Hayamizu, Iko Nakari, Hiroyuki Sato, Keiki Takadama: Inheritance vs. Expansion: Generalization Degree of Nearest Neighbor Rule in Continuous Space as Covering Operator of XCS, International Conference on the Applications of Evolutionary Computation, 2022. (Paper)

2021

  • Yohei Hayamizu, Saeid Amiri, Kishan Chandan, Keiki Takadama, Shiqi Zhang: Guiding robot exploration in reinforcement learning via automated planning, International Conference on Automated Planning and Scheduling (ICAPS), 2021. (Paper, Video)

  • Hiroki Shiraishi, Masakazu Tadokoro, Yohei Hayamizu, Yukiko Fukumoto, Hiroyuki Sato, and Keiki Takadama: Misclassification Detection based on Conditional VAE for Rule Evolution in Learning Classifier System, The Genetic and Evolutionary Computation Conference (GECCO), 2021. (Paper)

  • Hiroki Shiraishi, Masakazu Tadokoro, Yohei Hayamizu, Yukiko Fukumoto, Hiroyuki Sato, and Keiki Takadama: Increasing Accuracy and Interpretability of High-Dimensional Rules for Learning Classifier System, IEEE Congress on Evolutionary Computation (CEC), 2021. (Paper)

2020
  • Yohei Hayamizu, Saeid Amiri, Kishan Chandan, Keiki Takadama, Shiqi Zhang: Efficient Exploration in Reinforcement Learning Leveraging Automated Planning, The NeurIPS-2020 Workshop on Robot Learning, 2020. Paper, Video)
Awards
  • UEC Meguro-kai award: Awarded to Students who achieved excellent research outcomes at University of Electro-Communications (Top 5%)
  • President’s Award for Students: Awarded to Students who achieved excellent grades and outcomes at University of Electro-Communications (Top 10%)
  • SSI Excellent Paper Award, 2020 (Co-author), (Domestic Conference in Japan)
  • FIT Best Paper Award, 2020 (Domestic Conference in Japan)
  • ARLISS UNISEC Award 2018: Awarded to the team tackling the most challenging mission of over-back CanSat
  • Kusakari Award: Awarded to Students who achieved excellent grades and outcomes at Iwate University, 2020 (Top 5%)