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We show that given a desired closed-loop response for a system, there exists an affine subspace of controllers that achieve this response. By leveraging the existence of this subspace, we are able to separate controller design from…

Systems and Control · Electrical Eng. & Systems 2020-06-11 Jing Shuang Li , Dimitar Ho

Robust controller synthesis attracts reviving research interest, driven by the rise of learning-based systems where uncertainty and perturbation are ubiquitous. Facing an uncertain situation, a robustly stabilizing controller should…

Optimization and Control · Mathematics 2022-02-11 Shih-Hao Tseng

A major challenge faced in the design of large-scale cyber-physical systems, such as power systems, the Internet of Things or intelligent transportation systems, is that traditional distributed optimal control methods do not scale…

Optimization and Control · Mathematics 2017-01-23 Yuh-Shyang Wang , Nikolai Matni , John C. Doyle

Individual machines in flexible production lines explicitly expose capabilities at their interfaces by means of parametric skills. Given such a set of configurable machines, a line integrator is faced with the problem of finding and tuning…

Formal Languages and Automata Theory · Computer Science 2016-05-23 Chih-Hong Cheng , Lacramioara Astefanoaei , Harald Ruess , Souha Ben Rayana , Saddek Bensalem

Linear temporal logic (LTL) is a specification language for finite sequences (called traces) widely used in program verification, motion planning in robotics, process mining, and many other areas. We consider the problem of learning LTL…

Artificial Intelligence · Computer Science 2026-01-22 Ritam Raha , Rajarshi Roy , Nathanaël Fijalkow , Daniel Neider

Reinforcement learning (RL) is a powerful way to adapt foundation models to specialized tasks, but its reliance on large-scale human-labeled data limits broad adoption. We introduce Synthetic Data RL, a simple and general framework that…

Computation and Language · Computer Science 2025-05-26 Yiduo Guo , Zhen Guo , Chuanwei Huang , Zi-Ang Wang , Zekai Zhang , Haofei Yu , Huishuai Zhang , Yikang Shen

Despite achieving superior performance in human-level control problems, unlike humans, deep reinforcement learning (DRL) lacks high-order intelligence (e.g., logic deduction and reuse), thus it behaves ineffectively than humans regarding…

Artificial Intelligence · Computer Science 2022-05-30 Yushi Cao , Zhiming Li , Tianpei Yang , Hao Zhang , Yan Zheng , Yi Li , Jianye Hao , Yang Liu

Linear temporal logic (LTL) is a compelling framework for specifying complex, structured tasks for reinforcement learning (RL) agents. Recent work has shown that interpreting LTL instructions as finite automata, which can be seen as…

Artificial Intelligence · Computer Science 2025-12-03 Mattia Giuri , Mathias Jackermeier , Alessandro Abate

In this paper, we investigate the control synthesis problem for Signal Temporal Logic (STL) specifications in the presence of uncontrollable agents. Existing works mainly address this problem in a robust control setting by assuming the…

Systems and Control · Electrical Eng. & Systems 2025-02-21 Bohan Cui , Xinyi Yu , Alessandro Giua , Xiang Yin

We propose a Reinforcement Learning (RL) based control design framework for handling complex tasks. The approach extends the concept of Reward Machines (RM) with Signal Temporal Logic (STL) formulas that can be used for event generation.…

Artificial Intelligence · Computer Science 2026-04-17 Ana María Gómez Ruiz , Thao Dang , Alexandre Donzé

In the \emph{Adapter Design Pattern}, a programmer implements a \emph{Target} interface by constructing an \emph{Adapter} that accesses an existing \emph{Adaptee} code. In this work, we present a reactive synthesis interpretation to the…

Formal Languages and Automata Theory · Computer Science 2021-05-31 Gal Amram , Suguman Bansal , Dror Fried , Lucas M. Tabajara , Moshe Y. Vardi , Gera Weiss

Producing accurate software models is crucial in model-driven software engineering (MDE). However, modeling complex systems is an error-prone task that requires deep application domain knowledge. In the past decade, several automated…

Software Engineering · Computer Science 2024-08-27 Vittoriano Muttillo , Claudio Di Sipio , Riccardo Rubei , Luca Berardinelli , MohammadHadi Dehghani

In this paper, we propose a control synthesis method for signal temporal logic (STL) specifications with neural networks (NNs). Most of the previous works consider training a controller for only a given STL specification. These approaches,…

Systems and Control · Electrical Eng. & Systems 2022-12-13 Wataru Hashimoto , Kazumune Hashimoto , Masako Kishida , Shigemasa Takai

Recent studies have demonstrated that incorporating Chain-of-Thought (CoT) reasoning into the detection process can enhance a model's ability to detect synthetic images. However, excessively lengthy reasoning incurs substantial resource…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Changjiang Jiang , Xinkuan Sha , Fengchang Yu , Jingjing Liu , Jian Liu , Mingqi Fang , Chenfeng Zhang , Wei Lu

We formalize synthesis of shared control protocols with correctness guarantees for temporal logic specifications. More specifically, we introduce a modeling formalism in which both a human and an autonomy protocol can issue commands to a…

Robotics · Computer Science 2016-10-28 Nils Jansen , Murat Cubuktepe , Ufuk Topcu

Reactive synthesis aims at automatic construction of systems from their behavioural specifications. The research mostly focuses on synthesis of systems dealing with Boolean signals. But real-life systems are often described using…

Formal Languages and Automata Theory · Computer Science 2018-09-14 Ayrat Khalimov , Benedikt Maderbacher , Roderick Bloem

Synthesizing a reactive system from specifications given in linear temporal logic (LTL) is a classical problem, finding its applications in safety-critical systems design. We present our tool SemML, which won this year's LTL realizability…

Artificial Intelligence · Computer Science 2025-04-18 Jan Kretinsky , Tobias Meggendorfer , Maximilian Prokop , Ashkan Zarkhah

Test collections play a vital role in evaluation of information retrieval (IR) systems. Obtaining a diverse set of user queries for test collection construction can be challenging, and acquiring relevance judgments, which indicate the…

Information Retrieval · Computer Science 2024-05-14 Hossein A. Rahmani , Nick Craswell , Emine Yilmaz , Bhaskar Mitra , Daniel Campos

Practical guidance on training Large Language Models (LLMs) to leverage Code Interpreter across diverse tasks remains lacking. We present R1-Code-Interpreter, an extension of a text-only LLM trained via multi-turn supervised fine-tuning…

Artificial Intelligence · Computer Science 2026-03-05 Yongchao Chen , Yueying Liu , Junwei Zhou , Yilun Hao , Jingquan Wang , Yang Zhang , Na Li , Chuchu Fan
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