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We present two novel symbolic algorithms for model checking the Alternating-time Temporal Logic ATL*, over both the infinite-trace and the finite-trace semantics. In particular, for infinite traces we design a novel symbolic reduction to…

Logic in Computer Science · Computer Science 2025-10-22 Sofia Garcia de Blas Garcia-Alcalde , Francesco Belardinelli

We study dynamic changes of agents' observational power in logics of knowledge and time. We consider CTL*K, the extension of CTL* with knowledge operators, and enrich it with a new operator that models a change in an agent's way of…

Logic in Computer Science · Computer Science 2018-09-05 Aurèle Barrière , Bastien Maubert , Aniello Murano , Sasha Rubin

In this paper we introduce Epistemic Strategy Logic (ESL), an extension of Strategy Logic with modal operators for individual knowledge. This enhanced framework allows us to represent explicitly and to reason about the knowledge agents have…

Logic in Computer Science · Computer Science 2014-04-04 Francesco Belardinelli

Quite some work in the ATL-tradition uses the differences between various types of strategies (positional, uniform, perfect recall) to give alternative semantics to the same logical language. This paper contributes to another perspective on…

Logic in Computer Science · Computer Science 2016-07-13 Hein Duijf , Jan Broersen

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…

Logic in Computer Science · Computer Science 2018-09-05 Raphaël Berthon , Bastien Maubert , Aniello Murano , Sasha Rubin , Moshe Vardi

We propose an extension of Strategy Logic (SL), in which one can both reason about strategizing under imperfect information and about players' knowledge. One original aspect of our approach is that we do not force strategies to be uniform,…

Logic in Computer Science · Computer Science 2019-08-08 Sophia Knight , Bastien Maubert

Large-language models (LLMs) and chatbot agents are known to provide wrong outputs at times, and it was recently found that this can never be fully prevented. Hence, uncertainty quantification plays a crucial role, aiming to quantify the…

Machine Learning · Computer Science 2025-05-29 Michael Kirchhof , Gjergji Kasneci , Enkelejda Kasneci

We propose extending Alternating-time Temporal Logic (ATL) by an operator <i refines-to G> F to express that agent i can distribute its powers to a set of sub-agents G in a way which satisfies ATL condition f on the strategic ability of the…

Logic in Computer Science · Computer Science 2014-04-04 Dimitar P. Guelev

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, this problem is…

Logic in Computer Science · Computer Science 2020-03-11 Raphaël Berthon , Bastien Maubert , Aniello Murano , Sasha Rubin , Moshe Vardi

Natural language has long enabled human cooperation, but its lossy, ambiguous, and indirect nature limits the potential of collective intelligence. While machines are not subject to these constraints, most LLM-based multi-agent systems…

Machine Learning · Computer Science 2025-10-24 Yujia Zheng , Zhuokai Zhao , Zijian Li , Yaqi Xie , Mingze Gao , Lizhu Zhang , Kun Zhang

We present Stratified Metric Temporal Logic (SMTL), a novel formalism for specifying and verifying properties of complex cyber-physical systems that exhibit behaviors across multiple temporal and abstraction scales. SMTL extends existing…

Systems and Control · Electrical Eng. & Systems 2025-01-13 Ali Baheri , Peng Wei

Temporal epistemic logic is a well-established framework for expressing agents knowledge and how it evolves over time. Within language-based security these are central issues, for instance in the context of declassification. We propose to…

Cryptography and Security · Computer Science 2012-09-03 Musard Balliu , Mads Dam , Gurvan Le Guernic

Responsibility plays a key role in the development and deployment of trustworthy autonomous systems. In this paper, we focus on the problem of strategic reasoning in probabilistic multi-agent systems with responsibility-aware agents. We…

Artificial Intelligence · Computer Science 2024-12-23 Chunyan Mu , Muhammad Najib , Nir Oren

Attributional inference, the ability to predict latent intentions behind observed actions, is a critical yet underexplored capability for large language models (LLMs) operating in multi-agent environments. Traditional natural language…

Computation and Language · Computer Science 2026-01-14 Xin Quan , Jiafeng Xiong , Marco Valentino , André Freitas

While large language model (LLM) multi-agent systems achieve superior reasoning performance through iterative debate, practical deployment is limited by their high computational cost and error propagation. This paper proposes AgentArk, a…

Artificial Intelligence · Computer Science 2026-05-26 Yinyi Luo , Yiqiao Jin , Weichen Yu , Mengqi Zhang , Srijan Kumar , Xiaoxiao Li , Weijie Xu , Xin Chen , Jindong Wang

As learned control policies become increasingly common in autonomous systems, there is increasing need to ensure that they are interpretable and can be checked by human stakeholders. Formal specifications have been proposed as ways to…

Human-Computer Interaction · Computer Science 2024-07-04 Isabelle Hurley , Rohan Paleja , Ashley Suh , Jaime D. Peña , Ho Chit Siu

We propose a dynamic logic of lying, wherein a 'lie that phi' (where phi is a formula in the logic) is an action in the sense of dynamic modal logic, that is interpreted as a state transformer relative to the formula phi. The states that…

Artificial Intelligence · Computer Science 2012-03-22 Hans van Ditmarsch

Many complex scenarios require the coordination of agents possessing unique points of view and distinct semantic commitments. In response, standpoint logic (SL) was introduced in the context of knowledge integration, allowing one to reason…

Artificial Intelligence · Computer Science 2023-04-28 Nicola Gigante , Lucia {Gomez Alvarez} , Tim S. Lyon

Negotiation requires more than inferring what the other side wants: it requires using that information to make advantageous offers and counteroffers over multiple turns. We study whether large language model (LLM) agents do this in a…

Artificial Intelligence · Computer Science 2026-05-19 Romain Cosentino , Sarath Shekkizhar , Adam Earle , Silvio Savarese

The search for information on the web is faced with several problems, which arise on the one hand from the vast number of available sources, and on the other hand from their heterogeneity. A promising approach is the use of multi-agent…

Multiagent Systems · Computer Science 2007-05-23 T. Eiter , M. Fink , G. Sabbatini , H. Tompits