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Most works on multi-agent reinforcement learning focus on scenarios where the state of the environment is fully observable. In this work, we consider a cooperative policy evaluation task in which agents are not assumed to observe the…

Machine Learning · Computer Science 2023-05-17 Mert Kayaalp , Fatima Ghadieh , Ali H. Sayed

Propositional term modal logic is interpreted over Kripke structures with unboundedly many accessibility relations and hence the syntax admits variables indexing modalities and quantification over them. This logic is undecidable, and we…

Logic in Computer Science · Computer Science 2019-01-01 Anantha Padmanabha , R Ramanujam

There has been an increasing interest in topological semantics for epistemic logic, which has been shown to be useful for, e.g., modelling evidence, degrees of belief, and self-reference. We introduce a polytopological PDL capable of…

Logic in Computer Science · Computer Science 2026-02-17 Martín Diéguez , David Fernández-Duque

In multiagent systems autonomous agents interact with each other to achieve individual and collective goals. Typical interactions concern negotiation and agreement on resource exchanges. Modeling and formalizing these agreements pose…

Logic in Computer Science · Computer Science 2024-08-20 Lorenzo Ceragioli , Pierpaolo Degano , Letterio Galletta , Luca Viganò

We study a general class of dynamic multi-agent decision problems with asymmetric information and non-strategic agents, which includes dynamic teams as a special case. When agents are non-strategic, an agent's strategy is known to the other…

Multiagent Systems · Computer Science 2018-12-05 Hamidreza Tavafoghi , Yi Ouyang , Demosthenis Teneketzis

We consider the problem of classification with a (peer-to-peer) network of heterogeneous and partially informative agents, each receiving local data generated by an underlying true class, and equipped with a classifier that can only…

Machine Learning · Computer Science 2024-10-01 Tong Yao , Shreyas Sundaram

In the present paper syntax and semantics will be presented for an expansion of ordinary n-agent QML with constant domain, non-rigid constants, rigid variables and including both functions, relations, and equality. Further, the number of…

Logic in Computer Science · Computer Science 2018-11-06 Andreas Achen

We suggest a model of a multi-agent society of decision makers taking decisions being based on two criteria, one is the utility of the prospects and the other is the attractiveness of the considered prospects. The model is the…

Physics and Society · Physics 2018-01-17 V. I. Yukalov , E. P. Yukalova , D. Sornette

The Knowledge of Preconditions principle (KoP) is proposed as a widely applicable connection between knowledge and action in multi-agent systems. Roughly speaking, it asserts that if some condition is a necessary condition for performing a…

Multiagent Systems · Computer Science 2016-06-27 Yoram Moses

In the field of knowledge representation, the considered epistemic states are often based on propositional interpretations, also called worlds. E.g., epistemic states of agents can be modelled by ranking functions or total preorders on…

Artificial Intelligence · Computer Science 2022-03-29 Jonas Haldimann , Christoph Beierle

We present Dynamic Epistemic Temporal Logic, a framework for reasoning about operations on multi-agent Kripke models that contain a designated temporal relation. These operations are natural extensions of the well-known "action models" from…

Logic in Computer Science · Computer Science 2014-11-25 Bryan Renne , Joshua Sack , Audrey Yap

Many applications of intelligent systems require reasoning about the mental states of agents in the domain. We may want to reason about an agent's beliefs, including beliefs about other agents; we may also want to reason about an agent's…

Artificial Intelligence · Computer Science 2013-01-18 Brian Milch , Daphne Koller

This paper is an original attempt to understand the foundations of economic reasoning. It endeavors to rigorously define the relationship between subjective interpretations and objective valuations of such interpretations in the context of…

Logic in Computer Science · Computer Science 2024-05-20 Daniel Lu

Reasoning abilities of human beings are limited. Logics that treat logical inference for human knowledge should reflect these limited abilities. Logic of awareness is one of those logics. In the logic, what an agent with a limited reasoning…

Multiagent Systems · Computer Science 2024-02-14 Yudai Kubono

We study public announcement operators in the context of standard G\"odel modal logic as introduced by Caicedo and Rodriguez. Over that base logic, admitting a natural semantics over [0,1]-valued generalizations of modal Kripke models, we…

Logic · Mathematics 2021-12-15 Nicholas Pischke

We develop a modeling technique based on interpreted systems in order to verify temporal-epistemic properties over access control policies. This approach enables us to detect information flow vulnerabilities in dynamic policies by verifying…

Logic in Computer Science · Computer Science 2014-01-21 Masoud Koleini , Eike Ritter , Mark Ryan

The influence of additional information on the decision making of agents, who are interacting members of a society, is analyzed within the mathematical framework based on the use of quantum probabilities. The introduction of social…

Physics and Society · Physics 2015-10-12 V. I. Yukalov , D. Sornette

We study an intuitionistic version of common knowledge logic (CK), called ICK, which was introduced by J\"ager and Marti. ICK extends intuitionistic propositional logic (IPL) by multiple box modalities interpreted as knowledge operators for…

Logic · Mathematics 2026-05-04 Lukas Zenger

In dynamic epistemic logic (Van Ditmarsch, Van Der Hoek, & Kooi, 2008) it is customary to use an action frame (Baltag & Moss, 2004; Baltag, Moss, & Solecki, 1998) to describe different views of a single action. In this article, action…

Artificial Intelligence · Computer Science 2023-05-02 Shikha Singh , Kamal Lodaya , Deepak Khemani

This paper presents a distributed Koopman operator learning framework for modeling unknown nonlinear dynamics using sequential observations from multiple agents. Each agent estimates a local Koopman approximation based on lifted data and…

Systems and Control · Electrical Eng. & Systems 2026-04-21 Ali Azarbahram , Shenyu Liu , Gian Paolo Incremona