SWI-Prolog is neither a commercial Prolog system nor a purely academic enterprise, but increasingly a community project. The core system has been shaped to its current form while being used as a tool for building research prototypes, primarily for knowledge-intensive and interactive systems. Community contributions have added several interfaces and the constraint (CLP) libraries. Commercial involvement has created the initial garbage collector, added several interfaces and two development tools: PlDoc (a literate programming documentation system) and PlUnit (a unit testing environment).

In this article, we present SWI-Prolog as an integrating tool, supporting a wide range of ideas developed in the Prolog community and acting as glue between foreign resources. This article itself is the glue between technical articles on SWI-Prolog, providing context and experience in applying them over a longer period.

Swi-prolog

The paradigm of Tabled Logic Programming (TLP) is now supported by a number of Prolog systems, including XSB, YAP Prolog, B-Prolog, Mercury, ALS, and Ciao. The reasons for this are partly theoretical: tabling ensures termination and optimal known complexity for queries to a large class of programs. However, the overriding reasons are practical. TLP allows sophisticated programs to be written concisely and efficiently, especially when mechanisms such as tabled negation and call and answer subsumption are supported. As a result, TLP has now been used in a variety of applications from program analysis to querying over the semantic web. This paper provides a survey of TLP and its applications as implemented in the XSB Prolog, along with discussion of how XSB supports tabling with dynamically changing code, and in a multi-threaded environment.

/pdf/xsb-extending-prolog-with-tabled-logic-programming-33tmosjxsd.pdf

Xsb: Extending prolog with tabled logic programming

The paradigm of Tabled Logic Programming (TLP) is now supported by a number of Prolog systems, including XSB, YAP Prolog, B-Prolog, Mercury, ALS, and Ciao. The reasons for this are partly theoretical: tabling ensures termination and optimal known complexity for queries to a large class of programs. However the overriding reasons are practical. TLP allows sophisticated programs to be written concisely and efficiently, especially when mechanisms such as tabled negation and call and answer subsumption are supported. As a result TLP has now been used in a variety of applications from program analysis to querying over the semantic web. This paper provides a survey of TLP and its applications as implemented in XSB Prolog, along with discussion of how XSB supports tabling with dynamically changing code, and in a multi-threaded environment.

pdf/xsb-extending-prolog-with-tabled-logic-programming-2l20fvlp7v.pdf

XSB: Extending Prolog with Tabled Logic Programming

Normal logic programs.- Extended logic programs.- Why a new semantics for extended programs?.- WFSX - A well founded semantics for extended logic programs.- WFSX, LP semantics with two negations, and autoepistemic logics.- WFSX and default logic.- WFSX and hypotheses abduction.- Dealing with contradiction.- Further properties and comparisons.- Top-down derivation procedures for WFSX.- Application to classical nonmonotonic reasoning problems.- Application to diagnosis and debugging.

Reasoning with Logic Programming

Precisely when the success of artificial intelligence (AI) sub-symbolic techniques makes them be identified with the whole AI by many non-computer-scientists and non-technical media, symbolic approaches are getting more and more attention as those that could make AI amenable to human understanding. Given the recurring cycles in the AI history, we expect that a revamp of technologies often tagged as “classical AI”—in particular, logic-based ones—will take place in the next few years. On the other hand, agents and multi-agent systems (MAS) have been at the core of the design of intelligent systems since their very beginning, and their long-term connection with logic-based technologies, which characterised their early days, might open new ways to engineer explainable intelligent systems. This is why understanding the current status of logic-based technologies for MAS is nowadays of paramount importance. Accordingly, this paper aims at providing a comprehensive view of those technologies by making them the subject of a systematic literature review (SLR). The resulting technologies are discussed and evaluated from two different perspectives: the MAS and the logic-based ones.

/pdf/logic-based-technologies-for-multi-agent-systems-a-cpnf07c6bu.pdf

Logic-based technologies for multi-agent systems: a systematic literature review

InterProlog is the first Prolog-Java interface to support multiple Prolog systems through the same API; currently XSB and SWI Prolog, with GNU Prolog and YAP under development — on Windows, Linux and Mac OS X. It promotes coarse-grained integration between logic and object-oriented layers, by providing the ability to bidirectionally map any class data structure to a Prolog term; integration is done either through the Java Native Interface or TCP/IP sockets. It is proposed as a first step towards a common standard Java + Prolog API, gifting the Java developer with the best inference engines, and the logic programmer with simple access to the mainstream object-oriented platform.

/pdf/interprolog-towards-a-declarative-embedding-of-logic-25y1ysvxjh.pdf

InterProlog: Towards a Declarative Embedding of Logic Programming in Java

This paper extends the scope and optimality of previous algorithmic debugging techniques (i.e., diagnosis) of Prolog programs, amenable to realistic implementation. A new framework is set forth, the “Select&Query” algorithm schema. It provides a uniform treatment for more error types and a larger Prolog subset, including programs with comitments (“cuts”) and meta-logical predicates, though not side-effects. It can incorporate standard and also user-provided heuristics that profit from domain information. Integration with conventional execution browsers is easily accomplished.

A Framework for Prolog Debugging.

Programming environments have evolved from purely text based to using graphical user interfaces, and now we see a move towards web based interfaces, such as Jupyter. Web based interfaces allow for the creation of interactive documents that consist of text and programs, as well as their output. The output can be rendered using web technology as, e.g., text, tables, charts or graphs. This approach is particularly suitable for capturing data analysis workflows and creating interactive educational material. This article describes SWISH, a web front-end for Prolog that consists of a web server implemented in SWI-Prolog and a client web application written in JavaScript. SWISH provides a web server where multiple users can manipulate and run the same material, and it can be adapted to support Prolog extensions. In this paper we describe the architecture of SWISH, and describe two case studies of extensions of Prolog, namely Probabilistic Logic Programming (PLP) and Logic Production System (LPS), which have used SWISH to provide tutorial sites.

Using SWISH to realise interactive web based tutorials for logic based languages

Programming environments have evolved from purely text based to using graphical user interfaces, and now we see a move toward web-based interfaces, such as Jupyter. Web-based interfaces allow for the creation of interactive documents that consist of text and programs, as well as their output. The output can be rendered using web technology as, for example, text, tables, charts, or graphs. This approach is particularly suitable for capturing data analysis workflows and creating interactive educational material. This article describes SWISH, a web front-end for Prolog that consists of a web server implemented in SWI-Prolog and a client web application written in JavaScript. SWISH provides a web server where multiple users can manipulate and run the same material, and it can be adapted to support Prolog extensions. In this article we describe the architecture of SWISH, and describe two case studies of extensions of Prolog, namely Probabilistic Logic Programming and Logic Production System, which have used SWISH to provide tutorial sites.

/pdf/using-swish-to-realize-interactive-web-based-tutorials-for-1105r1zha9.pdf

Using SWISH to Realize Interactive Web-based Tutorials for Logic-based Languages

Prolog side-effects are typical necessary evil. Convenient logic program properties no longer hold, and upsetting practical problems sprout, namely the debugging of programs with side-effects is harder. This paper attempts to reduce the magnitude of such problems, by formulating a framework for the algorithmic debugging of logic programs with side-effects, encompassing both input/output (I/O) and internal database (DB) ones. Our debugging framework [Pereira Calejo 88] is reviewed and extended for that purpose. The new methods extend the scope and differ, significantly, from those developed in the context of [Pereira 84 86].

Algorithmic Debugging of Prolog Side-Effects

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