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相关论文: Refining and Delegating Strategic Ability in ATL

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We introduce versions of game-theoretic semantics (GTS) for Alternating-Time Temporal Logic (ATL). In GTS, truth is defined in terms of existence of a winning strategy in a semantic evaluation game, and thus the game-theoretic perspective…

逻辑 · 数学 2019-06-18 Valentin Goranko , Antti Kuusisto , Raine Rönnholm

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…

机器人学 · 计算机科学 2024-12-31 Hao Zhang , Hao Wang , Xiucai Huang , Wenrui Chen , Zhen Kan

When developing reinforcement learning agents, the standard approach is to train an agent to converge to a fixed policy that is as close to optimal as possible for a single fixed reward function. If different agent behaviour is required in…

多智能体系统 · 计算机科学 2021-01-29 David O'Callaghan , Patrick Mannion

Tasks with complex temporal structures and long horizons pose a challenge for reinforcement learning agents due to the difficulty in specifying the tasks in terms of reward functions as well as large variances in the learning signals. We…

人工智能 · 计算机科学 2018-09-27 Xiao Li , Yao Ma , Calin Belta

This paper presents a comprehensive framework for run-time self-checking of logical agents, by means of temporal axioms to be dynamically checked. These axioms are specified by using an agent-oriented interval temporal logic defined to this…

人工智能 · 计算机科学 2021-11-10 Stefania Costantini

Large Language Models (LLMs) increasingly rely on agentic capabilities-iterative retrieval, tool use, and decision-making-to overcome the limits of static, parametric knowledge. Yet existing agentic frameworks treat external information as…

计算与语言 · 计算机科学 2026-04-24 Yuanfu Sun , Kang Li , Dongzhe Fan , Jiajin Liu , Qiaoyu Tan

We introduce a new family of temporal logics designed to finely balance the trade-off between expressivity and complexity. Their key feature is the possibility of defining operators of a new kind that we call transformation operators. Some…

计算机科学中的逻辑 · 计算机科学 2024-09-09 Alessandro Ronca

The paper studies problems of satisfiability, decidability and admissibility of inference rules, conceptions of knowledge and agent's knowledge in non-transitive temporal linear logic LTL(Past,m). We find algorithms solving mentioned…

计算机科学中的逻辑 · 计算机科学 2014-06-12 Vladimir Rybakov

We consider the problem of computing the set of initial states of a dynamical system such that there exists a control strategy to ensure that the trajectories satisfy a temporal logic specification with probability 1 (almost-surely). We…

系统与控制 · 计算机科学 2015-02-24 Maria Svorenova , Jan Kretinsky , Martin Chmelik , Krishnendu Chatterjee , Ivana Cerna , Calin Belta

This paper introduces a logic with a class of social network models that is based on standard Linear Temporal Logic (LTL), leveraging the power of existing model checkers for the analysis of social networks. We provide a short literature…

社会与信息网络 · 计算机科学 2021-03-15 Vitor Machado , Mario Benevides

This paper describes a technique for inferring temporal-logic properties for sets of finite data streams. Such data streams arise in many domains, including server logs, program testing, and financial and marketing data; temporal-logic…

计算机科学中的逻辑 · 计算机科学 2020-06-09 Samuel Huang , Rance Cleaveland

We introduce a new translation from linear temporal logic (LTL) to deterministic Emerson-Lei automata, which are omega-automata with a Muller acceptance condition symbolically expressed as a Boolean formula. The richer acceptance condition…

形式语言与自动机理论 · 计算机科学 2017-09-08 David Müller , Salomon Sickert

Autonomous agents powered by large language models (LLMs) enable novel use cases in domains where responsible action is increasingly important. Yet the inherent unpredictability of LLMs raises safety concerns about agent reliability. In…

人工智能 · 计算机科学 2025-05-19 Jan Chojnacki

We propose a distributed control and coordination strategy for multi-agent systems where each agent has a local task specified as a Linear Temporal Logic (LTL) formula and at the same time is subject to relative-distance constraints with…

多智能体系统 · 计算机科学 2014-11-03 Meng Guo , Jana Tumova , Dimos V. Dimarogonas

In this paper we give automata-based representation of LTL-FO$^+$ properties. LTL-FO$^+$ is an extension of LTL that includes first-order quantification over bounded variable, thus greatly increasing the expressivity of the language. An…

形式语言与自动机理论 · 计算机科学 2016-10-25 Yannick Lebrun , Raphaël Khoury , Sylvain Hallé

We introduce an extension of Strategy Logic for the imperfect-information setting, called SLii, and study its model-checking problem. As this logic naturally captures multi-player games with imperfect information, the problem turns out to…

计算机科学中的逻辑 · 计算机科学 2018-09-05 Raphaël Berthon , Bastien Maubert , Aniello Murano , Sasha Rubin , Moshe Vardi

We introduce and study a natural extension of the Alternating time temporal logic ATL, called Temporal Logic of Coalitional Goal Assignments (TLCGA). It features just one, but quite expressive, coalitional strategic operator, viz. the…

计算机科学中的逻辑 · 计算机科学 2022-02-24 Sebastian Enqvist , Valentin Goranko

In a previous work we introduced Dual Light Affine Logic (DLAL) ([BaillotTerui04]) as a variant of Light Linear Logic suitable for guaranteeing complexity properties on lambda-calculus terms: all typable terms can be evaluated in polynomial…

计算机科学中的逻辑 · 计算机科学 2007-05-23 Vincent Atassi , Patrick Baillot , Kazushige Terui

We consider the setting of stochastic multiagent systems modelled as stochastic multiplayer games and formulate an automated verification framework for quantifying and reasoning about agents' trust. To capture human trust, we work with a…

计算机科学中的逻辑 · 计算机科学 2019-05-17 Xiaowei Huang , Marta Kwiatkowska , Maciej Olejnik

Strategic reasoning enables agents to cooperate, communicate, and compete with other agents in diverse situations. Existing approaches to solving strategic games rely on extensive training, yielding strategies that do not generalize to new…

人工智能 · 计算机科学 2023-05-31 Kanishk Gandhi , Dorsa Sadigh , Noah D. Goodman