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We propose a logic of interactive proofs as a framework for an intuitionistic foundation for interactive computation, which we construct via an interactive analog of the Goedel-McKinsey-Tarski-Artemov definition of Intuitionistic Logic as…

Logic in Computer Science · Computer Science 2017-08-09 Simon Kramer

In this paper, a pragmatic semantic communication framework that enables effective goal-oriented information sharing between two-intelligent agents is proposed. In particular, semantics is defined as the causal state that encapsulates the…

Information Theory · Computer Science 2023-12-01 Christo Kurisummoottil Thomas , Emilio Calvanese Strinati , Walid Saad

Topological data analysis (TDA) is a branch of computational mathematics, bridging algebraic topology and data science, that provides compact, noise-robust representations of complex structures. Deep neural networks (DNNs) learn millions of…

Despite the recent advancement in the social robotic field, important limitations restrain its progress and delay the application of robots in everyday scenarios. In the present paper, we propose to develop computational models inspired by…

Robotics · Computer Science 2019-09-04 Francesca Bianco , Dimitri Ognibene

Quantum simulation has become a promising avenue of research that allows one to simulate and gain insight into the models of High Energy Physics whose experimental realizations are either complicated or inaccessible with current technology.…

High Energy Physics - Phenomenology · Physics 2023-08-01 S. Hasibul Hassan Chowdhury , Talal Ahmed Chowdhury , Salah Nasri , Omar Ibna Nazim , Shaikh Saad

The TTE approach to Computable Analysis is the study of so-called representations (encodings for continuous objects such as reals, functions, and sets) with respect to the notions of computability they induce. A rich variety of such…

Computational Complexity · Computer Science 2023-06-22 Carsten Rösnick-Neugebauer

We extend intersection types to a computational $\lambda$-calculus with algebraic operations \`a la Plotkin and Power. We achieve this by considering monadic intersections, whereby computational effects appear not only in the operational…

Programming Languages · Computer Science 2024-01-24 Francesco Gavazzo , Riccardo Treglia , Gabriele Vanoni

Turing computability is the standard computability paradigm which captures the computational power of digital computers. To understand whether one can create physically realistic devices which have super-Turing power, one needs to…

Logic · Mathematics 2021-10-01 Daniel S. Graça , Ning Zhong

In the previous work, we have given a novel, game-semantic model of computation in an intrinsic, non-inductive and non-axiomatic manner, which is similar to Turing machines but beyond computation on natural numbers, e.g., higher-order…

Logic in Computer Science · Computer Science 2019-12-17 Norihiro Yamada

In this paper, we continue the efforts of the Computational Theory of Intelligence (CTI) by extending concepts to include computational processes in terms of Genetic Algorithms (GA's) and Turing Machines (TM's). Active, Passive, and Hybrid…

Neural and Evolutionary Computing · Computer Science 2014-12-22 Daniel Kovach

Infinite time Turing machines extend the operation of ordinary Turing machines into transfinite ordinal time. By doing so, they provide a natural model of infinitary computability, a theoretical setting for the analysis of the power and…

Logic · Mathematics 2007-05-23 Joel David Hamkins

Persistent homology is currently one of the more widely known tools from computational topology and topological data analysis. We present in this note a brief survey on the evolution of the subject. The goal is to highlight the main ideas,…

Algebraic Topology · Mathematics 2018-10-02 Jose A. Perea

Processing-In-Memory (PIM) is a novel approach that augments existing DRAM memory chips with lightweight logic. By allowing to offload computations to the PIM system, this architecture allows for circumventing the data-bottleneck problem…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-01-18 André Lopes , Daniel Castro , Paolo Romano

We survey concepts at the frontier of research connecting artificial, animal and human cognition to computation and information processing---from the Turing test to Searle's Chinese Room argument, from Integrated Information Theory to…

Artificial Intelligence · Computer Science 2015-12-25 Nicolas Gauvrit , Hector Zenil , Jesper Tegnér

Superintegrable systems are classical and quantum Hamiltonian systems which enjoy much symmetry and structure that permit their solubility via analytic and even, algebraic means. They include such well-known and important models as the…

Mathematical Physics · Physics 2012-09-26 Amelia L. Yzaguirre

This paper is about conceptual modeling of aggregates in software engineering. An aggregate is a cluster of domain objects that can be treated as a single unit. In UML, an aggregation is a type of association in which objects are configured…

Software Engineering · Computer Science 2022-08-25 Sabah Al-Fedaghi

The deterministic many-interacting-worlds method proposed in 2014 showed potential among the numerous interpretation of quantum mechanics. The successful application of this method in harmonic oscillator has been promoted for a long time.…

Quantum Physics · Physics 2026-05-29 Wen Chen , An Min Wang

In topological quantum computing, information is encoded in "knotted" quantum states of topological phases of matter, thus being locked into topology to prevent decay. Topological precision has been confirmed in quantum Hall liquids by…

Quantum Algebra · Mathematics 2017-12-06 Eric C. Rowell , Zhenghan Wang

We consider the computational model of the Queue Automaton. An old result is that the deterministic queue automaton is equally expressive as the Turing machine. We introduced the Reactive Turing Machine, enhancing the Turing machine with a…

Formal Languages and Automata Theory · Computer Science 2025-02-13 Jos C. M. Baeten , Bas Luttik

Tsetlin Machines (TMs) have emerged as a compelling alternative to conventional deep learning methods, offering notable advantages such as smaller memory footprint, faster inference, fault-tolerant properties, and interpretability. Although…

Machine Learning · Computer Science 2024-11-14 K. Darshana Abeyrathna , Sara El Mekkaoui , Andreas Hafver , Christian Agrell