Learning interaction rules from multi-animal trajectories via augmented behavioral models. - Keisuke Fujii 001; Naoya Takeishi; Kazushi Tsutsui; Emyo Fujioka; Nozomi Nishiumi; Ryoya Tanaka; Mika Fukushiro; Kaoru Ide; Hiroyoshi Kohno; Ken Yoda; Susumu Takahashi; Shizuko Hiryu; et al. (NeurIPS, 2021)

Flexible prediction of opponent motion with internal representation in interception behavior. - Kazushi Tsutsui; Keisuke Fujii 001; Kazutoshi Kudo; Kazuya Takeda (Biol. Cybern., 2021)

Emergence of Collaborative Hunting via Multi-Agent Deep Reinforcement Learning. - Kazushi Tsutsui; Kazuya Takeda; Keisuke Fujii 001 (ICPR Workshops (1), 2022)

Evaluation of Creating Scoring Opportunities for Teammates in Soccer via Trajectory Prediction. - Masakiyo Teranishi; Kazushi Tsutsui; Kazuya Takeda; Keisuke Fujii 001 (MLSA@PKDD/ECML, 2022)

Location analysis of players in UEFA EURO 2020 and 2022 using generalized valuation of defense by estimating probabilities. - Rikuhei Umemoto; Kazushi Tsutsui; Keisuke Fujii 001 (CoRR, 2022)

Action Valuation of On- and Off-Ball Soccer Players Based on Multi-Agent Deep Reinforcement Learning. - Hiroshi Nakahara; Kazushi Tsutsui; Kazuya Takeda; Keisuke Fujii 001 (IEEE Access, 2023)

Runner re-identification from single-view video in the open-world setting. - Tomohiro Suzuki; Kazushi Tsutsui; Kazuya Takeda; Keisuke Fujii 001 (CoRR, 2023)

Adaptive Action Supervision in Reinforcement Learning from Real-World Multi-Agent Demonstrations. - Keisuke Fujii 001; Kazushi Tsutsui; Atom Scott; Hiroshi Nakahara; Naoya Takeishi; Yoshinobu Kawahara (ICAART (2), 2024)

Runner re-identification from single-view running video in the open-world setting. - Tomohiro Suzuki; Kazushi Tsutsui; Kazuya Takeda; Keisuke Fujii 001 (Multim. Tools Appl., 2024)