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We introduce the notion of an ACP process algebra. The models of the axiom system ACP are the origin of this notion. ACP process algebras have to do with processes in which no data are involved. We also introduce the notion of a meadow…

Rings and Algebras · Mathematics 2009-02-04 J. A. Bergstra , C. A. Middelburg

This article presents a general solution to the problem of computational complexity. First, it gives a historical introduction to the problem since the revival of the foundational problems of mathematics at the end of the 19th century.…

Computational Complexity · Computer Science 2023-12-25 Rami Zaidan

Process calculi based in logic, such as $\pi$DILL and CP, provide a foundation for deadlock-free concurrent programming, but exclude non-determinism and races. HCP is a reformulation of CP which addresses a fundamental shortcoming: the…

Logic in Computer Science · Computer Science 2023-06-22 Wen Kokke , J. Garrett Morris , Philip Wadler

The major challenge in designing a discriminative learning algorithm for predicting structured data is to address the computational issues arising from the exponential size of the output space. Existing algorithms make different assumptions…

Machine Learning · Computer Science 2010-06-29 Shankar Vembu

Basic Parallel Processes (BPPs) are a well-known subclass of Petri Nets. They are the simplest common model of concurrent programs that allows unbounded spawning of processes. In the probabilistic version of BPPs, every process generates…

Logic in Computer Science · Computer Science 2014-01-17 Rémi Bonnet , Stefan Kiefer , Anthony W. Lin

Probabilistic programming makes it easy to represent a probabilistic model as a program. Building an individual model, however, is only one step of probabilistic modeling. The broader challenge of probabilistic modeling is in understanding…

Programming Languages · Computer Science 2022-08-15 Ryan Bernstein

The computational burden of probabilistic inference remains a hurdle for applying probabilistic programming languages to practical problems of interest. In this work, we provide a semantic and algorithmic foundation for efficient exact…

Programming Languages · Computer Science 2019-07-02 Steven Holtzen , Todd Millstein , Guy Van den Broeck

The generation of comprehensible explanations is an essential feature of modern artificial intelligence systems. In this work, we consider probabilistic logic programming, an extension of logic programming which can be useful to model…

Artificial Intelligence · Computer Science 2023-08-17 Germán Vidal

Alignment algorithms usually rely on simplified models of gaps for computational efficiency. Based on an isomorphism between alignments and physical helix-coil models, we show in statistical mechanics that alignments with realistic laws for…

Genomics · Quantitative Biology 2015-06-26 E. Yeramian , E. Debonneuil

Current decision support systems address domains that are heterogeneous in nature and becoming progressively larger. Such systems often require the input of expert judgement about a variety of different fields and an intensive computational…

Other Statistics · Statistics 2017-07-10 Manuele Leonelli , Eva Riccomagno , Jim Q. Smith

Truly concurrent process algebras are generalizations to the traditional process algebras for true concurrency, CTC to CCS, APTC to ACP, $\pi_{tc}$ to $\pi$ calculus , APPTC to probabilistic process algebra. And we also did some work on…

Logic in Computer Science · Computer Science 2021-08-09 Yong Wang

Influence diagrams provide a compact graphical representation of decision problems. Several algorithms for the quick computation of their associated expected utilities are available in the literature. However, often they rely on a full…

Artificial Intelligence · Computer Science 2017-01-19 Manuele Leonelli , Eva Riccomagno , Jim Q. Smith

We sketch a process algebra with data and probability distributions. This allows to combine two very powerful abstraction mechanisms namely non-deterministic choice and probabilities. However, it is not clear how to define an appropriate…

Logic in Computer Science · Computer Science 2021-08-25 Jan Friso Groote

Many models in natural language processing define probabilistic distributions over linguistic structures. We argue that (1) the quality of a model' s posterior distribution can and should be directly evaluated, as to whether probabilities…

Computation and Language · Computer Science 2015-09-03 Khanh Nguyen , Brendan O'Connor

There are many different models of concurrent processes. The goal of this work is to introduce a common formalized framework for current research in this area and to eliminate shortcomings of existing models of concurrency. Following up the…

Logic in Computer Science · Computer Science 2008-03-24 Mark Burgin a , Marc L. Smith

Assumption-based argumentation (ABA) is a central structured argumentation formalism. As shown recently, answer set programming (ASP) enables efficiently solving NP-hard reasoning tasks of ABA in practice, in particular in the commonly…

Artificial Intelligence · Computer Science 2021-08-10 Tuomo Lehtonen , Johannes P. Wallner , Matti Järvisalo

Forward inference techniques such as sequential Monte Carlo and particle Markov chain Monte Carlo for probabilistic programming can be implemented in any programming language by creative use of standardized operating system functionality…

Artificial Intelligence · Computer Science 2014-07-11 Brooks Paige , Frank Wood

Compositionality is a key property for dealing with complexity, which has been studied from many points of view in diverse fields. Particularly, the composition of individual computations (or programs) has been widely studied almost since…

Logic in Computer Science · Computer Science 2022-06-06 Damian Arellanes

Threads as considered in basic thread algebra are primarily looked upon as behaviours exhibited by sequential programs on execution. It is a fact of life that sequential programs are often fragmented. Consequently, fragmented program…

Logic in Computer Science · Computer Science 2011-06-17 J. A. Bergstra , C. A. Middelburg

Checklists have been widely recognized as effective tools for completing complex tasks in a systematic manner. Although originally intended for use in procedural tasks, their interpretability and ease of use have led to their adoption for…

Machine Learning · Computer Science 2024-11-27 Yukti Makhija , Edward De Brouwer , Rahul G. Krishnan