7 citations · 7 across the 4 of their papers we have counts for
7 papers · 1 filter
Learning-based Bounded Synthesis for Semi-MDPs with LTL Specifications
Ryohei Oura, Toshimitsu Ushio
This letter proposes a learning-based bounded synthesis for a semi-Markov decision process (SMDP) with a linear temporal logic (LTL) specification. In the product of the SMDP and t…
Collaborative rover-copter path planning and exploration with temporal logic specifications based on Bayesian update under uncertain environments
Kazumune Hashimoto, Natsuko Tsumagari, Toshimitsu Ushio
This paper investigates a collaborative rover-copter path planning and exploration with temporal logic specifications under uncertain environments. The objective of the rover is to…
On-Line Synthesis of Permissive Supervisors for Partially Observed Discrete Event Systems under scLTL Constraints
Ami Sakakibara, Toshimitsu Ushio
We consider a supervisory control problem of a discrete event system (DES) under partial observation, where a control specification is given by a fragment of linear temporal logic.…
Reinforcement Learning of Control Policy for Linear Temporal Logic Specifications Using Limit-Deterministic Generalized Büchi Automata
Ryohei Oura, Ami Sakakibara, Toshimitsu Ushio
This letter proposes a novel reinforcement learning method for the synthesis of a control policy satisfying a control specification described by a linear temporal logic formula. We…
Control of Timed Discrete Event Systems with Ticked Linear Temporal Logic Constraints
Takuma Kinugawa, Kazumune Hashimoto, Toshimitsu Ushio
This paper presents a novel method of synthesizing a fragment of a timed discrete event system(TDES),introducing a novel linear temporal logic(LTL), called ticked LTL. The tick…
Learning self-triggered controllers with Gaussian processes
Kazumune Hashimoto, Yuichi Yoshimura, Toshimitsu Ushio
This paper investigates the design of self-triggered controllers for networked control systems (NCSs), where the dynamics of the plant is \textit{unknown} apriori. To deal with the…