Universal Constructions for (Co)Relations: categories, monoidal categories, and props

Calculi of string diagrams are increasingly used to present the syntax and algebraic structure of various families of circuits, including signal flow graphs, electrical circuits and quantum processes. In many such approaches, the semantic interpretation for diagrams is given in terms of relations or corelations (generalised equivalence relations) of some kind. In this paper we show how semantic categories of both relations and corelations can be characterised as colimits of simpler categories. This modular perspective is important as it simplifies the task of giving a complete axiomatisation for semantic equivalence of string diagrams. Moreover, our general result unifies various theorems that are independently found in literature and are relevant for program semantics, quantum computation and control theory.Comment: 22 pages + 3 page appendix, extended version of arXiv:1703.0824

Termination of canonical context-sensitive rewriting and productivity of rewrite systems

[EN] Termination of programs, i.e., the absence of infinite computations, ensures the existence of normal forms for all initial expressions, thus providing an essential ingredient for the definition of a normalization semantics for functional programs. In lazy functional languages, though, infinite data structures are often delivered as the outcome of computations. For instance, the list of all prime numbers can be returned as a neverending stream of numerical expressions or data structures. If such streams are allowed, requiring termination is hopeless. In this setting, the notion of productivity can be used to provide an account of computations with infinite data structures, as it "captures the idea of computability, of progress of infinite-list programs" (B.A. Sijtsma, On the Productivity of Recursive List Definitions, ACM Transactions on Programming Languages and Systems 11(4):633-649, 1989). However, in the realm of Term Rewriting Systems, which can be seen as (first-order, untyped, unconditional) functional programs, termination of Context-Sensitive Rewriting (CSR) has been showed equivalent to productivity of rewrite systems through appropriate transformations. In this way, tools for proving termination of CSR can be used to prove productivity. In term rewriting, CSR is the restriction of rewriting that arises when reductions are allowed on selected arguments of function symbols only. In this paper we show that well-known results about the computational power of CSR are useful to better understand the existing connections between productivity of rewrite systems and termination of CSR, and also to obtain more powerful techniques to prove productivity of rewrite systems.Partially supported by the EU (FEDER), Spanish MINECO TIN 2013-45732-C4-1-P, and GV PROMETEOII/2015/013.Lucas Alba, S. (2015). Termination of canonical context-sensitive rewriting and productivity of rewrite systems. Electronic Proceedings in Theoretical Computer Science. 200:18-31. https://doi.org/10.4204/EPTCS.200.2S183120

A coalgebraic perspective on probabilistic logic programming

Probabilistic logic programming is increasingly important in artificial intelligence and related fields as a formalism to reason about uncertainty. It generalises logic programming with the possibility of annotating clauses with probabilities. This paper proposes a coalgebraic perspective on probabilistic logic programming. Programs are modelled as coalgebras for a certain functor F, and two semantics are given in terms of cofree coalgebras. First, the cofree F-coalgebra yields a semantics in terms of derivation trees. Second, by embedding F into another type G, as cofree G-coalgebra we obtain a “possible worlds” interpretation of programs, from which one may recover the usual distribution semantics of probabilistic logic programming

Synthesis of models for order-sorted first-order theories using linear algebra and constraint solving

[EN] Recent developments in termination analysis for declarative programs emphasize the use of appropriate models for the logical theory representing the program at stake as a generic approach to prove termination of declarative programs. In this setting, Order-Sorted First-Order Logic provides a powerful framework to represent declarative programs. It also provides a target logic to obtain models for other logics via transformations. We investigate the automatic generation of numerical models for order-sorted first-order logics and its use in program analysis, in particular in termination analysis of declarative programs. We use convex domains to give domains to the different sorts of an order-sorted signature; we interpret the ranked symbols of sorted signatures by means of appropriately adapted convex matrix interpretations. Such numerical interpretations permit the use of existing algorithms and tools from linear algebra and arithmetic constraint solving to synthesize the models.Partially supported by the EU (FEDER), Spanish MINECO TIN 2013-45732-C4-1-P and GV PROMETEOII/2015/013Lucas Alba, S. (2015). Synthesis of models for order-sorted first-order theories using linear algebra and constraint solving. Electronic Proceedings in Theoretical Computer Science. 200:32-47. https://doi.org/10.4204/EPTCS.200.3S324720

A Coalgebraic Perspective on Probabilistic Logic Programming

Probabilistic logic programming is increasingly important in artificial intelligence and related fields as a formalism to reason about uncertainty. It generalises logic programming with the possibility of annotating clauses with probabilities. This paper proposes a coalgebraic perspective on probabilistic logic programming. Programs are modelled as coalgebras for a certain functor F, and two semantics are given in terms of cofree coalgebras. First, the cofree F-coalgebra yields a semantics in terms of derivation trees. Second, by embedding F into another type G, as cofree G-coalgebra we obtain a "possible worlds" interpretation of programs, from which one may recover the usual distribution semantics of probabilistic logic programming

Coalgebraic Semantics for Probabilistic Logic Programming

Probabilistic logic programming is increasingly important in artificial intelligence and related fields as a formalism to reason about uncertainty. It generalises logic programming with the possibility of annotating clauses with probabilities. This paper proposes a coalgebraic semantics on probabilistic logic programming. Programs are modelled as coalgebras for a certain functor F, and two semantics are given in terms of cofree coalgebras. First, the F-coalgebra yields a semantics in terms of derivation trees. Second, by embedding F into another type G, as cofree G-coalgebra we obtain a `possible worlds' interpretation of programs, from which one may recover the usual distribution semantics of probabilistic logic programming. Furthermore, we show that a similar approach can be used to provide a coalgebraic semantics to weighted logic programming

Coalgebraic semantics for probabilistic logic programming

Probabilistic logic programming is increasingly important in artificial intelligence and related fields as a formalism to reason about uncertainty. It generalises logic programming with the possibility of annotating clauses with probabilities. This paper proposes a coalgebraic semantics on probabilistic logic programming. Programs are modelled as coalgebras for a certain functor F, and two semantics are given in terms of cofree coalgebras. First, the cofree F-coalgebra yields a semantics in terms of derivation trees. Second, by embedding F into another type G, as cofree G-coalgebra we obtain a 'possible worlds' interpretation of programs, from which one may recover the usual distribution semantics of probabilistic logic programming. Furthermore, we show that a similar approach can be used to provide a coalgebraic semantics to weighted logic programming

Comprobación de modelos en sistemas concurrentes a partir de su semántica en Maude

La comprobación de modelos (model checking) es una técnica automática para verificar si una propiedad se cumple en un sistema concurrente. Maude es un marco lógico de alto rendimiento donde se puede especificar, modelar, ejecutar y analizar —de forma sencilla— otros sistemas. Además, este entorno incluye un comprobador de modelos para verificar propiedades expresadas en lógica temporal lineal. Sin embargo, cuando una propiedad aplicada a un programa —escrito en un lenguaje de programación modelado para Maude— no se cumple, el contraejemplo —generado por el propio sistema— está basado en la semántica del propio Maude, dificultando la tarea de poder seguirlo a la hora de entender el resultado. En esta memoria presentamos la herramienta Selene, un marco genérico que maneja sistemas concurrentes asíncronos de modo que el usuario pueda obtener una versión simplificada de los contraejemplos generados por el comprobador de modelos en Maude tras la realización del análisis sobre programas escritos en otros lenguajes. Para lograrlo se ofrece un kernel para manejar la memoria y los mensajes, elementos que se emplearán en el “informe” final obtenido del contraejemplo. Sobre dicha arquitectura el usuario podrá especificar los detalles de la semántica del lenguaje a manejar. Por último, se analizará cuáles fueron los objetivos iniciales, los resultados obtenidos, los problemas encontrados durante el desarrollo, así como las propuestas y líneas futuras de trabajo que serían deseables para la mejora del proyecto