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We provide algebraic semantics together with a sound and complete sequent calculus for information update due to epistemic actions. This semantics is flexible enough to accommodate incomplete as well as wrong information e.g.due to secrecy…

Logic · Mathematics 2007-05-23 Alexandru Baltag , Bob Coecke , Mehrnoosh Sadrzadeh

Real-valued logics underlie an increasing number of neuro-symbolic approaches, though typically their logical inference capabilities are characterized only qualitatively. We provide foundations for establishing the correctness and power of…

Logic in Computer Science · Computer Science 2022-09-01 Ronald Fagin , Ryan Riegel , Alexander Gray

We introduce a generic, compositional and interpretable class of generative world models that supports open-ended learning agents. This is a sparse class of Bayesian networks capable of approximating a broad range of stochastic processes,…

Artificial Intelligence · Computer Science 2024-10-16 Lancelot Da Costa

This paper makes a first step towards a logic of learning from experiments. For this, we investigate formal frameworks for modeling the interaction of causal and (qualitative) epistemic reasoning. Crucial for our approach is the idea that…

Artificial Intelligence · Computer Science 2021-12-02 Fausto Barbero , Katrin Schulz , Fernando R. Velázquez-Quesada , Kaibo Xie

Recent ideas about epistemic modals and indicative conditionals in formal semantics have significant overlap with ideas in modal logic and dynamic epistemic logic. The purpose of this paper is to show how greater interaction between formal…

Logic in Computer Science · Computer Science 2017-08-07 Wesley H. Holliday , Thomas F. Icard

We describe an algorithm for automatic classification of idiomatic and literal expressions. Our starting point is that words in a given text segment, such as a paragraph, that are highranking representatives of a common topic of discussion…

Computation and Language · Computer Science 2018-02-28 Jing Peng , Anna Feldman , Ekaterina Vylomova

Traditional neural networks have an impressive classification performance, but what they learn cannot be inspected, verified or extracted. Neural Logic Networks on the other hand have an interpretable structure that enables them to learn a…

Machine Learning · Computer Science 2026-01-26 Vincent Perreault , Katsumi Inoue , Richard Labib , Alain Hertz

Substantial efforts have been made in developing various Decision Modeling formalisms, both from industry and academia. A challenging problem is that of expressing decision knowledge in the context of incomplete knowledge. In such contexts,…

Artificial Intelligence · Computer Science 2023-12-19 Đorđe Marković , Simon Vandevelde , Linde Vanbesien , Joost Vennekens , Marc Denecker

Epistemic planning can be used for decision making in multi-agent situations with distributed knowledge and capabilities. Recently, Dynamic Epistemic Logic (DEL) has been shown to provide a very natural and expressive framework for…

Artificial Intelligence · Computer Science 2017-03-08 Thorsten Engesser , Thomas Bolander , Robert Mattmüller , Bernhard Nebel

It is demonstrated that under the hypothesis of boundedness, the semantics appears as a property of spontaneous physical processes. It turns that both semantic structure and semantic meaning have their own physical agents each of which is…

General Physics · Physics 2010-09-09 Maria K. Koleva

This paper exhibits a series of semantic characterisations of sublinear nondeterministic complexity classes. These results fall into the general domain of logic-based approaches to complexity theory and so-called implicit computational…

Logic in Computer Science · Computer Science 2016-09-27 Thomas Seiller

We consider dynamic versions of epistemic logic as formulated in Baltag and Moss "Logics for epistemic programs" (2004). That paper proposed a logical language (actually families of languages parameterized by action signatures) for dynamic…

Logic in Computer Science · Computer Science 2022-03-15 Alexandru Baltag , Lawrence S. Moss , Slawomir Solecki

In this paper, we develop a representation-theoretic formulation of discrete-time linear systems. We show that such systems are naturally viewed as representations of time groups acting on vector spaces, thereby endowing the state space…

Systems and Control · Electrical Eng. & Systems 2026-04-13 Subhrajit Sinha

Epistemic logics model how agents reason about their beliefs and the beliefs of other agents. Existing logics typically assume the ability of agents to reason perfectly about propositions of unbounded modal depth. We present DBEL, an…

Artificial Intelligence · Computer Science 2023-07-17 Farid Arthaud , Martin Rinard

We argue that an explainable artificial intelligence must possess a rationale for its decisions, be able to infer the purpose of observed behaviour, and be able to explain its decisions in the context of what its audience understands and…

Artificial Intelligence · Computer Science 2021-04-26 Michael Timothy Bennett , Yoshihiro Maruyama

Despite the fact that beliefs are mental states that cannot be directly observed, humans talk about each others' beliefs on a regular basis, often using rich compositional language to describe what others think and know. What explains this…

Artificial Intelligence · Computer Science 2024-07-10 Lance Ying , Tan Zhi-Xuan , Lionel Wong , Vikash Mansinghka , Joshua Tenenbaum

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

This article provides an algebraic study of intermediate inquisitive and dependence logics. While these logics are usually investigated using team semantics, here we introduce an alternative algebraic semantics and we prove it is complete…

Logic · Mathematics 2023-03-21 Davide Emilio Quadrellaro

In formal epistemology, group knowledge is often modelled as the knowledge that the group would have, if the agents shared all their individual knowledge. However, this interpretation does not account for relations between agents. In this…

Logic in Computer Science · Computer Science 2024-03-28 Christian Cachin , David Lehnherr , Thomas Studer

In this paper, we advocate the use of stratified logical theories for representing probabilistic models. We argue that such encodings can be more interpretable than those obtained in existing frameworks such as Markov logic networks. Among…

Artificial Intelligence · Computer Science 2016-11-21 Ondrej Kuzelka , Jesse Davis , Steven Schockaert
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