4 papers
Data-Driven Synthesis of Probabilistic Controlled Invariant Sets for Linear MDPs
Kazumune Hashimoto, Shunki Kimura, Kazunobu Serizawa +3
We study data-driven computation of probabilistic controlled invariant sets (PCIS) for safety-critical reinforcement learning under unknown dynamics. Assuming a linear MDP model, w…
Receding-Horizon Maximum-Likelihood Estimation of Neural-ODE Dynamics and Thresholds from Event Cameras
Kazumune Hashimoto, Kazunobu Serizawa, Masako Kishida
Event cameras emit asynchronous brightness-change events where each pixel triggers an event when the last event exceeds a threshold, yielding a history-dependent measurement model.…
Structural-Ambiguity-Aware Translation from Natural Language to Signal Temporal Logic
Kosei Fushimi, Kazunobu Serizawa, Junya Ikemoto +1
Signal Temporal Logic (STL) is widely used to specify timed and safety-critical tasks for cyber-physical systems, but writing STL formulas directly is difficult for non-expert user…
Clustering-based Recurrent Neural Network Controller synthesis under Signal Temporal Logic Specifications
Kazunobu Serizawa, Kazumune Hashimoto, Wataru Hashimoto +2
Autonomous robotic systems require advanced control frameworks to achieve complex temporal objectives that extend beyond conventional stability and trajectory tracking. Signal Temp…