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Top-performing machine learning systems, such as deep neural networks, large ensembles and complex probabilistic graphical models, can be expensive to store, slow to evaluate and hard to integrate into larger systems. Ideally, we would like…

Machine Learning · Statistics 2015-10-09 George Papamakarios

In modern machine learning, pattern recognition replaces realtime semantic reasoning. The mapping from input to output is learned with fixed semantics by training outcomes deliberately. This is an expensive and static approach which depends…

Artificial Intelligence · Computer Science 2017-08-02 Mark Burgess

We develop an incremental-tableau-based decision procedure for the multi-agent epistemic logic MAEL(CD) (aka S5_n (CD)), whose language contains operators of individual knowledge for a finite set Ag of agents, as well as operators of…

Logic in Computer Science · Computer Science 2016-11-17 Valentin Goranko , Dmitry Shkatov

We consider a logic used to describe sets of configurations of distributed systems, whose network topologies can be changed at runtime, by reconfiguration programs. The logic uses inductive definitions to describe networks with an unbounded…

Logic in Computer Science · Computer Science 2022-04-27 Marius Bozga , Lucas Bueri , Radu Iosif

In the logic programming paradigm, a program is defined by a set of methods, each of which can be executed when specific conditions are met during the current state of an execution. The semantics of these programs can be elegantly…

Logic in Computer Science · Computer Science 2024-10-02 Matteo Acclavio , Roberto Maieli

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

Compositional generalization is a basic and essential intellective capability of human beings, which allows us to recombine known parts readily. However, existing neural network based models have been proven to be extremely deficient in…

Artificial Intelligence · Computer Science 2020-10-27 Qian Liu , Shengnan An , Jian-Guang Lou , Bei Chen , Zeqi Lin , Yan Gao , Bin Zhou , Nanning Zheng , Dongmei Zhang

Distributed knowledge is a key concept in the standard epistemic logic of knowledge-that. In this paper, we propose a corresponding notion of distributed knowledge-how and study its logic. Our framework generalizes two existing traditions…

Logic in Computer Science · Computer Science 2025-12-01 Bin Liu , Yanjing Wang

We introduce and study single-conclusioned nested sequent calculi for a broad class of intuitionistic multi-modal logics known as "intuitionistic grammar logics (IGLs)." These logics serve as the intuitionistic counterparts of classical…

Logic in Computer Science · Computer Science 2026-05-06 Tim S. Lyon

Epistemic graphs are a generalization of the epistemic approach to probabilistic argumentation. Hunter proposed a 2-way generalization framework to learn epistemic constraints from crowd-sourcing data. However, the learnt epistemic…

Artificial Intelligence · Computer Science 2023-06-08 Xiao Chi

Computing many useful properties of Boolean formulas, such as their weighted or unweighted model count, is intractable on general representations. It can become tractable when formulas are expressed in a special form, such as the decision…

Logic in Computer Science · Computer Science 2025-01-23 Randal E. Bryant , Wojciech Nawrocki , Jeremy Avigad , Marijn J. H. Heule

Combining deep neural networks with structured logic rules is desirable to harness flexibility and reduce uninterpretability of the neural models. We propose a general framework capable of enhancing various types of neural networks (e.g.,…

Machine Learning · Computer Science 2020-08-11 Zhiting Hu , Xuezhe Ma , Zhengzhong Liu , Eduard Hovy , Eric Xing

Our manuscript studies linear temporal (with UNTIL and NEXT) logic based at a conception of intransitive time. non-transitive time. In particular, we demonstrate how the notion of knowledge might be represented in such a framework (here we…

Logic in Computer Science · Computer Science 2015-03-31 Vladimir Rybakov

Common knowledge and only knowing capture two intuitive and natural notions that have proven to be useful in a variety of settings, for example to reason about coordination or agreement between agents, or to analyse the knowledge of…

Logic in Computer Science · Computer Science 2023-06-07 Marcos Cramer , Samuele Pollaci , Bart Bogaerts

As multi-agent AI systems evolve from simple chatbots to autonomous swarms, debugging semantic failures requires reasoning about knowledge, belief, causality, and obligation, precisely what modal logic was designed to formalize. However,…

Artificial Intelligence · Computer Science 2026-02-13 Antonin Sulc

Cognitive BASIC is a minimal, BASIC-style prompting language and in-model interpreter that structures large language model (LLM) reasoning into explicit, stepwise execution traces. Inspired by the simplicity of retro BASIC, we repurpose…

Artificial Intelligence · Computer Science 2025-11-24 Oliver Kramer

Awareness has been shown to be a useful addition to standard epistemic logic for many applications. However, standard propositional logics for knowledge and awareness cannot express the fact that an agent knows that there are facts of which…

Logic in Computer Science · Computer Science 2007-05-23 Joseph Y. halpern , Leandro Chaves Rego

In this paper, we discuss models of the common knowledge logic. The common knowledge logic is a multi-modal logic that includes the modal operators $\mathsf{K}_{i}$ ($i\in\mathcal{I}$, where $\mathcal{I}$ is a finite set of agents) and…

Logic · Mathematics 2025-12-23 Yoshihito Tanaka

Epistemic protocol specifications allow programs, for settings in which multiple agents act with incomplete information, to be described in terms of how actions are related to what the agents know. They are a variant of the knowledge-based…

Logic in Computer Science · Computer Science 2016-02-04 Xiaowei Huang , Ron van der Meyden

Knowledge-enhanced text generation aims to enhance the quality of generated text by utilizing internal or external knowledge sources. While language models have demonstrated impressive capabilities in generating coherent and fluent text,…

Computation and Language · Computer Science 2026-01-15 Shuqi Liu , Han Wu , Guanzhi Deng , Jianshu Chen , Xiaoyang Wang , Linqi Song