4 papers
Application of Deep Reinforcement Learning to Event-Triggered Control for Networked Artificial Pancreas Systems
Junya Ikemoto, Satoshi Maruyama, Kazumune Hashimoto
This paper proposes a deep reinforcement learning (DRL)-based event-triggered controller design for networked artificial pancreas (AP) systems. Although existing DRL-based AP contr…
Soft Switching Expert Policies for Controlling Systems with Uncertain Parameters
Junya Ikemoto
This paper proposes a simulation-based reinforcement learning algorithm for controlling systems with uncertain and varying system parameters. While simulators are useful for safely…
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…
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…