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There has been a considerable amount of work on uncertainty in knowledge-based systems. This work has generally been concerned with uncertainty arising from the strength of inferences and the weight of evidence. In this paper we discuss…

Artificial Intelligence · Computer Science 2013-04-12 Steven J. Henkind

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

We compare different epistemic notions in the presence of awareness of propositional variables: the logics of implicit knowledge (in which explicit knowledge is definable), explicit knowledge, and speculative knowledge. Different notions of…

Logic in Computer Science · Computer Science 2013-10-29 Hans van Ditmarsch , Tim French , Fernando R. Velazquez-Quesada , Yi N. Wang

Automata with monitor counters, where the transitions do not depend on counter values, and nested weighted automata are two expressive automata-theoretic frameworks for quantitative properties. For a well-studied and wide class of…

Formal Languages and Automata Theory · Computer Science 2023-06-22 Krishnendu Chatterjee , Thomas A. Henzinger , Jan Otop

Call a semantics for a language with variables absolute when variables map to fixed entities in the denotation. That is, a semantics is absolute when the denotation of a variable a is a copy of itself in the denotation. We give a trio of…

Logic in Computer Science · Computer Science 2026-04-20 Murdoch J. Gabbay

We propose an entropy function for simplicial complices. Its value gives the expected cost of the optimal encoding of sequences of vertices of the complex, when any two vertices belonging to the same simplex are indistinguishable. We show…

Information Theory · Computer Science 2016-03-24 Stefan Dantchev , Ioannis Ivrissimtzis

Large Language Models (LLMs) increasingly serve as autonomous reasoning agents in decision support, scientific problem-solving, and multi-agent coordination systems. However, deploying LLM agents in consequential applications requires…

Artificial Intelligence · Computer Science 2026-03-17 I. de Zarzà , J. de Curtò , Jordi Cabot , Pietro Manzoni , Carlos T. Calafate

Multilingual semantic parsing aims to leverage the knowledge from the high-resource languages to improve low-resource semantic parsing, yet commonly suffers from the data imbalance problem. Prior works propose to utilize the translations by…

Computation and Language · Computer Science 2023-05-23 Zhuang Li , Lizhen Qu , Philip R. Cohen , Raj V. Tumuluri , Gholamreza Haffari

Choice constructs are an important part of the language of logic programming, yet the study of their semantics has been a challenging task. So far, only two-valued semantics have been studied, and the different proposals for such semantics…

Artificial Intelligence · Computer Science 2024-08-01 Jesse Heyninck

We present and evaluate a technique for computing path-sensitive interference conditions during abstract interpretation of concurrent programs. In lieu of fixed point computation, we use prime event structures to compactly represent causal…

Programming Languages · Computer Science 2017-05-02 Marcelo Sousa , César Rodríguez , Vijay D'Silva , Daniel Kroening

Embodied agents operating in multi-agent, partially observable, and decentralized environments must plan and act despite pervasive uncertainty about hidden objects and collaborators' intentions. Recent advances in applying Large Language…

Artificial Intelligence · Computer Science 2026-02-05 SeungWon Seo , SooBin Lim , SeongRae Noh , Haneul Kim , HyeongYeop Kang

There is an apparent similarity between the descriptions of small-step operational semantics of imperative programs and the semantics of finite automata, so defining an abstraction mapping from semantics to automata and proving a simulation…

Programming Languages · Computer Science 2014-09-30 Nadezhda Baklanova , Wilmer Ricciotti , Jan-Georg Smaus , Martin Strecker

We consider the problem of a principal who needs to elicit the true worth of an object she owns from an agent who has a unique ability to compute this information. The correctness of the information cannot be verified by the principal, so…

Computer Science and Game Theory · Computer Science 2020-09-15 Shani Alkobi , David Sarne , Erel Segal-Halevi , Tomer Sharbaf

Representing meaning in the form of high dimensional vectors is a common and powerful tool in biologically inspired architectures. While the meaning of a set of concepts can be summarized by taking a (possibly weighted) sum of their…

Artificial Intelligence · Computer Science 2018-09-25 Douglas Summers-Stay , Peter Sutor , Dandan Li

Semantic communication is an emerging paradigm that focuses on understanding and delivering semantics, or meaning of messages. Most existing semantic communication solutions define semantic meaning as the meaning of object labels recognized…

Networking and Internet Architecture · Computer Science 2022-03-17 Jingming Liang , Yong Xiao , Yingyu Li , Guangming Shi , Mehdi Bennis

The framework of algorithmic knowledge assumes that agents use algorithms to compute the facts they explicitly know. In many cases of interest, a deductive system, rather than a particular algorithm, captures the formal reasoning used by…

Artificial Intelligence · Computer Science 2007-05-23 Riccardo Pucella

A formal but intuitive framework is introduced to bridge the gap between data obtained from empirical studies and that generated by agent-based models. This is based on three key tenets. Firstly, a simulation can be given multiple formal…

Multiagent Systems · Computer Science 2013-02-21 Chih-Chun Chen

We study here fundamental issues involved in top-k query evaluation in probabilistic databases. We consider simple probabilistic databases in which probabilities are associated with individual tuples, and general probabilistic databases in…

Databases · Computer Science 2009-06-08 Xi Zhang , Jan Chomicki

Mathematics is a limited component of solutions to real-world problems, as it expresses only what is expected to be true if all our assumptions are correct, including implicit assumptions that are omnipresent and often incorrect.…

Methodology · Statistics 2023-09-14 Sander Greenland

Invariant representations are core to representation learning, yet a central challenge remains: uncovering invariants that are stable and transferable without suppressing task-relevant signals. This raises fundamental questions, requiring…

Machine Learning · Computer Science 2025-09-29 Arun Kumar , Paul Schrater
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