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We introduce a sound and complete coinductive proof system for reachability properties in transition systems generated by logically constrained term rewriting rules over an order-sorted signature modulo builtins. A key feature of the…

Logic in Computer Science · Computer Science 2018-04-24 Ştefan Ciobâcă , Dorel Lucanu

Prediction algorithms assign numbers to individuals that are popularly understood as individual "probabilities" -- what is the probability of 5-year survival after cancer diagnosis? -- and which increasingly form the basis for life-altering…

Machine Learning · Computer Science 2020-11-30 Cynthia Dwork , Michael P. Kim , Omer Reingold , Guy N. Rothblum , Gal Yona

We establish the undecidability of conditional affine information inequalities, the undecidability of the conditional independence implication problem with a constraint that one random variable is binary, and the undecidability of the…

Information Theory · Computer Science 2022-02-11 Cheuk Ting Li

It can be argued that the ordinary description of the reversible quantum process between two one-to-one correlated measurement outcomes is incomplete because, by not specifying the direction of causality, it allows causal structures that…

Quantum Physics · Physics 2023-11-02 Giuseppe Castagnoli

Here we continue with the ideas expressed in "On the strangeness of quantum mechanics" aiming to demonstrate more concretely how this philosophical outlook might be used as a key for resolving the measurement problem. We will address in…

Quantum Physics · Physics 2023-03-13 Marcello Poletti

This paper examines two related problems that are central to developing an autonomous decision-making agent, such as a robot. Both problems require generating structured representafions from a database of unstructured declarative knowledge…

Artificial Intelligence · Computer Science 2013-04-10 Spencer Star

Uncertainty may be taken to characterize inferences, their conclusions, their premises or all three. Under some treatments of uncertainty, the inferences itself is never characterized by uncertainty. We explore both the significance of…

Artificial Intelligence · Computer Science 2013-02-18 Henry E. Kyburg

In this paper we consider a fragment of the first-order theory of the real numbers that includes systems of equations of continuous functions in bounded domains, and for which all functions are computable in the sense that it is possible to…

Computational Complexity · Computer Science 2016-08-15 Peter Franek , Stefan Ratschan , Piotr Zgliczynski

We study the difficulty of computing topological entropy of subshifts subjected to mixing restrictions. This problem is well-studied for multidimensional subshifts of finite type : there exists a threshold in the irreducibility rate where…

Dynamical Systems · Mathematics 2019-04-05 Silvère Gangloff , Benjamin Hellouin de Menibus

We identify a fundamental incompatibility between the goals of accuracy, trust, and human-level reasoning in artificial intelligence (AI) systems, for strict mathematical definitions of these notions. We define accuracy of a system as the…

Machine Learning · Computer Science 2026-05-11 Rina Panigrahy , Vatsal Sharan

Different types of reasoning impose different structural demands on representational systems, yet no systematic account of these demands exists across psychology, AI, and philosophy of mind. I propose a framework identifying four structural…

Artificial Intelligence · Computer Science 2026-04-03 Yiling Wu

In this paper we consider propositional calculi, which are finitely axiomatizable extensions of intuitionistic implicational propositional calculus together with the rules of modus ponens and substitution. We give a proof of undecidability…

Logic · Mathematics 2015-09-25 Grigoriy V. Bokov

The classical notions of structural controllability and structural observability are receiving increasing attention in Network Science, since they provide a mathematical basis to answer how the network structure of a dynamic system affects…

Systems and Control · Computer Science 2018-12-13 Marco Tulio Angulo , Andrea Aparicio , Claude H. Moog

Beginning with Turing's seminal work in 1950, artificial intelligence proposes that consciousness can be simulated by a Turing machine. This implies a potential theory of everything where the universe is a simulation on a computer, which…

Computational Complexity · Computer Science 2022-06-15 Blake Wilson , Ethan Dickey , Vaishnavi Iyer , Sabre Kais

Can a problem undecidable with classical resources be decidable with quantum ones? The answer expected is no; as both being Turing theories, they should not solve the Halting problem - a problem unsolvable by any Turing machine. Yet, we…

Quantum Physics · Physics 2021-12-28 Airin Antony

We report a new limitation on the ability of physical systems to perform computation -- one that is based on generalizing the notion of memory, or storage space, available to the system to perform the computation. Roughly, we define memory…

Computational Complexity · Computer Science 2019-05-15 Mark Braverman , Cristobal Rojas , Jonathan Schneider

Any system that models the world under finite representational capacity must compress; any compression entails a prior; and the prior is the system's bias. What has not been established is whether uncertainty participates in the dynamics…

Machine Learning · Computer Science 2026-05-20 Ahmed Gamal Eldin

The Turing machine halting problem can be explained by several factors, including arithmetic logic irreversibility and memory erasure, which contribute to computational uncertainty due to information loss during computation. Essentially,…

Other Computer Science · Computer Science 2023-03-28 Yair Lapin

Observability is a modelling property that describes the possibility of inferring the internal state of a system from observations of its output. A related property, structural identifiability, refers to the theoretical possibility of…

Quantitative Methods · Quantitative Biology 2018-12-12 Alejandro F. Villaverde

We introduce computational causal inference as an interdisciplinary field across causal inference, algorithms design and numerical computing. The field aims to develop software specializing in causal inference that can analyze massive…

Computation · Statistics 2020-07-22 Jeffrey C. Wong