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We show that alternating Turing machines, with a novel and natural definition of acceptance, accept precisely the inductive (Pi-1-1) languages. Total alternating machines, that either accept or reject each input, accept precisely the…

Logic in Computer Science · Computer Science 2015-07-01 Daniel M Leivant

We study Turing machines that are allowed absolutely no space overhead. The only work space the machines have, beyond the fixed amount of memory implicit in their finite-state control, is that which they can create by cannibalizing the…

Computational Complexity · Computer Science 2007-05-23 Lane A. Hemaspaandra , Proshanto Mukherji , Till Tantau

We consider notions of space complexity for Infinite Time Turing Machines (ITTMs) that were introduced by B. L\"owe and studied further by J. Winter. We answer several open questions about these notions, among them whether low space…

Logic · Mathematics 2026-05-19 Merlin Carl

The Curry-Howard correspondence is often called the proofs-as-programs result. I offer a generalization of this result, something which may be called machines as programs. Utilizing this insight, I introduce two new Turing Machines called…

Computational Complexity · Computer Science 2021-09-23 Jonathan J. Mize

We develop a complexity theory for approximate real computations. We first produce a theory for exact computations but with condition numbers. The input size depends on a condition number, which is not assumed known by the machine. The…

Computational Complexity · Computer Science 2020-05-05 Gregorio Malajovich , Mike Shub

We study a polynomial-time decision problem in which each input encodes a depth-$N$ causal execution in which a single non-duplicable token must traverse an ordered sequence of steps, revealing at most $O(1)$ bits of routing information at…

Optimization and Control · Mathematics 2026-03-27 Jing-Yuan Wei

We show how complexity theory can be introduced in machine learning to help bring together apparently disparate areas of current research. We show that this new approach requires less training data and is more generalizable as it shows…

Machine Learning · Computer Science 2019-10-10 Santiago Hernández-Orozco , Hector Zenil , Jürgen Riedel , Adam Uccello , Narsis A. Kiani , Jesper Tegnér

We develop techniques to investigate relativized hierarchical unambiguous computation. We apply our techniques to generalize known constructs involving relativized unambiguity based complexity classes (UP and \mathcal{UP}) to new constructs…

Computational Complexity · Computer Science 2007-05-23 Holger Spakowski , Rahul Tripathi

The complexity class $\exists\mathbb R$, standing for the complexity of deciding the existential first order theory of the reals as real closed field in the Turing model, has raised considerable interest in recent years. It is well known…

Computational Complexity · Computer Science 2025-02-04 Klaus Meer , Adrian Wurm

A language is dense if the set of all infixes (or subwords) of the language is the set of all words. Here, it is shown that it is decidable whether the language accepted by a nondeterministic Turing machine with a one-way read-only input…

Formal Languages and Automata Theory · Computer Science 2019-03-08 Oscar H. Ibarra , Ian McQuillan

We consider a nonlinear stochastic partial differential equation (SPDE) in divergence form where the forcing term is a Gaussian noise, that is white in time and colored in space such that the gradient of the solution is H\"older-continuous,…

Analysis of PDEs · Mathematics 2022-02-03 Florian Kunick

Abstract State Machines (ASMs) provide a model of computations on structures rather than strings. Blass, Gurevich and Shelah showed that deterministic PTIME-bounded ASMs define the choiceless fragment of PTIME, but cannot capture PTIME. In…

Logic in Computer Science · Computer Science 2024-01-30 Flavio Ferrarotti , Klaus-Dieter Schewe

A resource-bounded version of the statement "no algorithm recognizes all non-halting Turing machines" is equivalent to an infinitely often (i.o.) superpolynomial speedup for the time required to accept any coNP-complete language and also…

Computational Complexity · Computer Science 2012-09-24 Hunter Monroe

Probabilistic Circuits (PCs) are deep generative models that support exact and efficient probabilistic inference. Yet in autoregressive language modeling, PCs still lag behind Transformer-based large language models (LLMs), suggesting an…

Machine Learning · Computer Science 2026-05-14 Zhiyu Zhao , Xuejie Liu , Muhan Zhang , Anji Liu

We show that the decision problem for the basic system of interpretability logic IL is PSPACE-complete. For this purpose we present an algorithm which uses polynomial space with respect to the complexity of a given formula. The existence of…

Logic · Mathematics 2018-04-09 Luka Mikec , Fedor Pakhomov , Mladen Vuković

Deep neural networks (DNNs) have made significant strides in Natural Language Processing (NLP), yet their interpretability remains elusive, particularly when evaluating their intricate decision-making processes. Traditional methods often…

Computation and Language · Computer Science 2025-12-05 Zhou Yang , Shunyan Luo , Jiazhen Zhu , Fang Jin

Programming language concepts are used to give some new perspectives on a long-standing open problem: is logspace = ptime ?

Computational Complexity · Computer Science 2020-08-10 Neil D. Jones , Siddharth Bhaskar , Cynthia Kop , Jakob Grue Simonsen

This paper develops a Multiset Rewriting language with explicit time for the specification and analysis of Time-Sensitive Distributed Systems (TSDS). Goals are often specified using explicit time constraints. A good trace is an infinite…

Computational Complexity · Computer Science 2021-09-16 Max Kanovich , Tajana Ban Kirigin , Vivek Nigam , Andre Scedrov , Carolyn Talcott

We study a generalized version of reversal bounded Turing machines where, apart from several tapes on which the number of head reversals is bounded by r(n), there are several further tapes on which head reversals remain unrestricted, but…

Computational Complexity · Computer Science 2007-05-23 Andre Hernich , Nicole Schweikardt

In this monograph, we study complexity classes that are defined using $O(\log n)$-space bounded non-deterministic Turing machines. We prove salient results of Computational Complexity in this topic such as the Immerman-Szelepcsenyi Theorem,…

Computational Complexity · Computer Science 2026-03-17 T. C. Vijayaraghavan