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Reinforcement Learning (RL) based methods have been increasingly explored for robot learning. However, RL based methods often suffer from low sampling efficiency in the exploration phase, especially for long-horizon manipulation tasks, and…

Robotics · Computer Science 2024-12-31 Hao Zhang , Hao Wang , Xiucai Huang , Wenrui Chen , Zhen Kan

Metric temporal logic (MTL) and timed propositional temporal logic (TPTL) are quantitative extensions of linear temporal logic, which are prominent and widely used in the verification of real-timed systems. It was recently shown that the…

Logic in Computer Science · Computer Science 2023-06-22 Shiguang Feng , Markus Lohrey , Karin Quaas

Signal Temporal Logic (STL) inference seeks to extract human-interpretable rules from time-series data, but existing methods lack formal confidence guarantees for the inferred rules. Conformal prediction (CP) is a technique that can provide…

Machine Learning · Computer Science 2025-10-23 Danyang Li , Yixuan Wang , Matthew Cleaveland , Mingyu Cai , Roberto Tron

Recent advances in large language models (LLMs) have shown that test-time scaling can substantially improve model performance on complex tasks, particularly in the coding domain. Under this paradigm, models use a larger token budget during…

Artificial Intelligence · Computer Science 2026-04-21 Jiaxin Fang , Runyuan He , Sahil Bhatia , Neel Gajare , Alvin Cheung

We introduce a hybrid spatiotemporal logic for automotive safety applications (HSTL), focused on highway driving. Spatiotemporal logic features specifications about vehicles throughout space and time, while hybrid logic enables precise…

Logic in Computer Science · Computer Science 2026-03-30 Radu-Florin Tulcan , Rose Bohrer , Yoàv Montacute , Kevin Zhou , Yusuke Kawamoto , Ichiro Hasuo

This paper presents a methodology for temporal logic verification of discrete-time stochastic systems. Our goal is to find a lower bound on the probability that a complex temporal property is satisfied by finite traces of the system.…

Systems and Control · Computer Science 2019-11-22 Pushpak Jagtap , Sadegh Soudjani , Majid Zamani

Hyperproperties allow one to specify properties of systems that inherently involve not single executions of the system, but several of them at once: observational determinism and non-inference are two examples of such properties used to…

Logic in Computer Science · Computer Science 2025-12-02 Samuel Graepler , Benjamin Monmege , Jean-Marc Talbot

Recent work has addressed using formulas in linear temporal logic (LTL) as specifications for agents planning in Markov Decision Processes (MDPs). We consider the inverse problem: inferring an LTL specification from demonstrated behavior…

Systems and Control · Computer Science 2017-11-02 Daniel Kasenberg , Matthias Scheutz

The DL-Lite description logics allow for modeling domain knowledge on top of databases and for efficient reasoning. We focus on metric temporal extensions of DL-Lite_bool and its fragments, and study the complexity of satisfiability. In…

Logic in Computer Science · Computer Science 2018-08-08 Veronika Thost

Since the introduction of Alternating-time Temporal Logic (ATL), many logics have been proposed to reason about different strategic capabilities of the agents of a system. In particular, some logics have been designed to reason about the…

Logic in Computer Science · Computer Science 2017-09-08 Simon Busard , Charles Pecheur

Stochastic models such as Continuous-Time Markov Chains (CTMC) and Stochastic Hybrid Automata (SHA) are powerful formalisms to model and to reason about the dynamics of biological systems, due to their ability to capture the stochasticity…

Logic in Computer Science · Computer Science 2013-09-05 Ezio Bartocci , Luca Bortolussi , Laura Nenzi , Guido Sanguinetti

Hyperproperties, like observational determinism or symmetry, cannot be expressed as properties of individual computation traces, because they describe a relation between multiple computation traces. HyperLTL is a temporal logic that…

Logic in Computer Science · Computer Science 2016-06-23 Bernd Finkbeiner , Christopher Hahn

Timed temporal logics exhibit a bewildering diversity of operators and the resulting decidability and expressiveness properties also vary considerably. We study the expressive power of timed logics TPTL[U,S] and MTL[U,S] as well as of their…

Logic in Computer Science · Computer Science 2013-05-16 Paritosh K. Pandya , Simoni S. Shah

Test-Time Scaling (TTS) enhances the reasoning capabilities of large language models by allocating additional inference compute to explore the solution space. However, existing parallel TTS methods typically keep branches isolated during…

Computation and Language · Computer Science 2026-05-27 Xinglin Wang , Hao Lin , Shaoxiong Feng , Peiwen Yuan , Yiwei Li , Jiayi Shi , Yueqi Zhang , Chuyi Tan , Ji Zhang , Boyuan Pan , Yao Hu , Kan Li

Model Checking is widely applied in verifying the correctness of complex and concurrent systems against a specification. Pure symbolic approaches while popular, suffer from the state space explosion problem due to cross product operations…

Logic in Computer Science · Computer Science 2023-08-28 Prasita Mukherjee , Haoteng Yin

Model checking and automated theorem proving are two pillars of formal methods. This paper investigates model checking from an automated theorem proving perspective, aiming at combining the expressiveness of automated theorem proving and…

Logic in Computer Science · Computer Science 2017-10-03 Ying Jiang , Jian Liu , Gilles Dowek , Kailiang Ji

Linear temporal logic (LTL) is used in system verification to write formal specifications for reactive systems. However, some relevant properties, e.g. non-inference in information flow security, cannot be expressed in LTL. A class of such…

Logic in Computer Science · Computer Science 2024-06-10 Juha Kontinen , Max Sandström , Jonni Virtema

This paper establishes relative expressiveness results for several modal mu-calculi interpreted over timed automata. These mu-calculi combine modalities for expressing passage of (real) time with a general framework for defining formulas…

Logic in Computer Science · Computer Science 2025-08-08 Rance Cleaveland , Jeroen J. A. Keiren , Peter Fontana

Large Language Models (LLMs) increasingly rely on long-form, multi-step reasoning to solve complex tasks such as mathematical problem solving and scientific question answering. Despite strong performance, existing confidence estimation…

Computation and Language · Computer Science 2026-01-21 Zhenjiang Mao , Anirudhh Venkat , Artem Bisliouk , Akshat Kothiyal , Sindhura Kumbakonam Subramanian , Saithej Singhu , Ivan Ruchkin

We establish a correspondence between (fragments of) $\mathcal{TEL}^\bigcirc$, a temporal extension of the $\mathcal{EL}$ description logic with the LTL operator $\bigcirc^k$, and some specific kinds of formal grammars, in particular,…

Logic in Computer Science · Computer Science 2025-08-04 Camille Bourgaux , Anton Gnatenko , Michaël Thomazo