One of the first Prolog implementations made available by LPA was micro-PROLOG[2] which ran on popular 8-bit home computers such as the Sinclair ZX Spectrum[3] and Apple II.
The 8-bit micro-PROLOG interpreter was soon followed by micro-PROLOG Professional one of the first Prolog implementations for the IBM PC running MS-DOS. micro-PROLOG Professional could access all of the 640K memory available under MS-DOS and therefore manage much larger programs
In 1985, LPA released LPA MacProlog which ran on the MacPlus and Mac II computers which could access up to 4 Mb memory. MacProlog was later licensed to Quintus for re-distribution in the USA.
In 1989, LPA started work on a new 32-bit Prolog compiler which could use DOS-extender technology to access up to 4GB memory.
This became the basis for LPA Prolog for Windows, aka WIN-PROLOG, which was then released for Windows 3.0 in 1990.
As well as continuing with Prolog compiler technology development, LPA has a track record of creating innovative associated tools and products to address specific challenges and opportunities.
Flex Expert System toolkit
In 1989, in response to the rise of interest in Expert Systems and the emergence of products such as Crystal, GoldWorks, NExpert, LPA developed the Flex expert system toolkit, which incorporated frame-based reasoning with inheritance, rule-based programming and data-driven procedures. Flex has its own English-like Knowledge Specification Language (KSL) which means that knowledge and rules are defined in an easy-to-read and understand way.[5]
LPA supported Flex on Windows, DOS and Macintosh PCs, as an add-on toolkit to its various LPA Prolog systems and eanbled LPA to enter the then quick vibrant Expert Systems rules-market.
Flex was quickly established as the leading Prolog-based expert system toolkit and was licensed to other Prolog providors on other hardware platforms including Telecomputing Plc to supplement Top One on IBM and ICL mainframes.[6]
Other implementations included Quintec-Flex, Quintus Flex, Poplog Flex and BIM Flex which were all running on Unix and/or Vax/VMS platforms.
POPLOG-Flex was used to build BRAND EVALUATOR - an expert system to assist brand specialists in evaluating the worth of branded products[7]
Quintec-Flex was used to build a hybrid system for the non-linear dynamic analysis/design of coupled shear walls [8]
Flex was adopted by the Open University as part of its course T396, "Artificial intelligence for technology"[9] which was designed by Prof Adrian Hopgood. Some of the teaching material is now available on his AI tookit website.
Flex was also used by David A Ferrucci and Selmer Bringsjord in their storytelling machine, BRUTUS.[10]
PVG
In 1992, LPA helped set up the Prolog Vendors Group,[11] a not-for-profit organization whose aim was to help promote Prolog by making people aware of its usage in industry.
Business Integrity Ltd and Contract Express
Between 1996 and 1998, based on work co-funded through a DTI Smart award, LPA developed ScaffoldIT,[12][13] a tool for building dynamic documents and intelligent web sites. This technology, built using the LPA Prolog engine and associated ProWeb Server, was able to generate complex, personalised documents such as insurance policy schedules, legal contracts, and complex sales proposals, over the Web.
In 1999/2000, LPA helped set up Business Integrity Ltd, as a Joint Venture with Tarlo-Lyons, to bring the above document assembly technology to market. This product eventually became Contract Express. Contract Express became very popular amongst large law firms and was sold worldwide for both internal and external use.
Partners and GCs liked Contract Express because lawyers were able to quickly and accurately automate and update their legal templates in Word without requiring IT specialists to convert them into programs.
As a result of the commercial success of Contract Express, BIL was acquired by Thomson Reuters in 2015.[14]
The very early days of BIL are described by Clive Spenser here.[15]
VisiRule
In 2004, LPA launched VisiRule [16] a graphical tool for developing knowledge-based and decision support systems. VisiRule was described in IEEE Potentials in 2007 (see Drawing on your knowledge with VisiRule):
VisiRule has been used in various sectors, to build legal expert systems, machine diagnostic programs, medical and financial advice systems, etc.[citation needed]
In 2023, VisiRule was listed as one of the 5 best decision support software for large enterprises in 2024.[17]
Customers
For many years, LPA has worked closely with Valdis Krebs, an American-Latvian researcher, author, and consultant in the field of social and organizational network analysis. Valdis is the founder and chief scientist of Orgnet, and the creator of the popular Inflow [18] software package.
LPA Prolog and Flex were used to create Allergenius, an expert system for the interpretation of allergen microarray results. Rules representing the knowledge base (KB) were derived from the literature and specialized databases. The input data included the patient's ID and disease(s), the results of either a skin prick test or specific IgE assays and ISAC results. The output was a medical report.[19]
Related Research Articles
In artificial intelligence (AI), an expert system is a computer system emulating the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if–then rules rather than through conventional procedural programming code. Expert systems were among the first truly successful forms of AI software. They were created in the 1970s and then proliferated in the 1980s, being then widely regarded as the future of AI — before the advent of successful artificial neural networks. An expert system is divided into two subsystems: 1) a knowledge base, which represents facts and rules; and 2) an inference engine, which applies the rules to the known facts to deduce new facts, and can include explaining and debugging abilities.
Knowledge representation and reasoning is a field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can use to solve complex tasks, such as diagnosing a medical condition or having a natural-language dialog. Knowledge representation incorporates findings from psychology about how humans solve problems and represent knowledge, in order to design formalisms that make complex systems easier to design and build. Knowledge representation and reasoning also incorporates findings from logic to automate various kinds of reasoning.
Prolog is a logic programming language that has its origins in artificial intelligence, automated theorem proving and computational linguistics.
Poplog is a reflective, incrementally compiled software development computer programming integrated development environment and system platform for the programming languages POP-11, Common Lisp, Prolog, and Standard ML. It was created originally in the United Kingdom for teaching and research in artificial intelligence, at the University of Sussex, and later marketed as a commercial package for software development, teaching, and research. It was one of the initiatives supported for a time by the UK government-funded Alvey Programme.
The Fifth Generation Computer Systems was a 10-year initiative launched in 1982 by Japan's Ministry of International Trade and Industry (MITI) to develop computers based on massively parallel computing and logic programming. The project aimed to create an "epoch-making computer" with supercomputer-like performance and to establish a platform for future advancements in artificial intelligence. Although FGCS was ahead of its time, its ambitious goals ultimately led to commercial failure. However, on a theoretical level, the project significantly contributed to the development of concurrent logic programming.
The following outline is provided as an overview of and topical guide to software engineering:
In the field of artificial intelligence, an inference engine is a software component of an intelligent system that applies logical rules to the knowledge base to deduce new information. The first inference engines were components of expert systems. The typical expert system consisted of a knowledge base and an inference engine. The knowledge base stored facts about the world. The inference engine applied logical rules to the knowledge base and deduced new knowledge. This process would iterate as each new fact in the knowledge base could trigger additional rules in the inference engine. Inference engines work primarily in one of two modes either special rule or facts: forward chaining and backward chaining. Forward chaining starts with the known facts and asserts new facts. Backward chaining starts with goals, and works backward to determine what facts must be asserted so that the goals can be achieved.
Logic in computer science covers the overlap between the field of logic and that of computer science. The topic can essentially be divided into three main areas:
SWI-Prolog is a free implementation of the programming language Prolog, commonly used for teaching and semantic web applications. It has a rich set of features, libraries for constraint logic programming, multithreading, unit testing, GUI, interfacing to Java, ODBC and others, literate programming, a web server, SGML, RDF, RDFS, developer tools, and extensive documentation.
This is an alphabetical list of articles pertaining specifically to software engineering.
Knowledge-based engineering (KBE) is the application of knowledge-based systems technology to the domain of manufacturing design and production. The design process is inherently a knowledge-intensive activity, so a great deal of the emphasis for KBE is on the use of knowledge-based technology to support computer-aided design (CAD) however knowledge-based techniques can be applied to the entire product lifecycle.
Cris Kobryn (1952) is an American systems engineer and software engineer best known for leading international teams of vendors and users in defining the Unified Modeling Language (UML) v1 and v2 standards for software engineering, as well as the Systems Modeling Language (SysML) v1 standard for systems engineering. He is the Founder and CTO of PivotPoint Technology Corp., a systems and software engineering services company that he founded in 2003.
LispWorks is computer software, a proprietary implementation and integrated development environment (IDE) for the programming language Common Lisp. LispWorks was developed by the UK software company Harlequin Ltd., and first published in 1989. Harlequin ultimately spun off its Lisp division as Xanalys Ltd., which took over management and rights to LispWorks. In January 2005, the Xanalys Lisp team formed LispWorks Ltd. to market, develop, and support the software.
Prolog++ is an object-oriented toolkit for the Prolog logic programming language. It allows classes and class hierarchies to be created within Prolog programs.
ILOG S.A. was an international software company purchased and incorporated into IBM announced in January, 2009. It created enterprise software products for supply chain, business rule management, visualization and optimization. The main product line for Business Rules Management Systems (BRMS) has been rebranded as IBM Operational Decision Management. Many of the related components retain the ILOG brand as a part of their name.
The Ecosystem Management Decision Support (EMDS) system is an application framework for knowledge-based decision support of ecological analysis and planning at any geographic scale.
In information technology a reasoning system is a software system that generates conclusions from available knowledge using logical techniques such as deduction and induction. Reasoning systems play an important role in the implementation of artificial intelligence and knowledge-based systems.
d3web is a free, open-source platform for knowledge-based systems. Its core is written in Java using XML and/or Office-based formats for the knowledge storage. All of its components are distributed under the terms of the Lesser General Public Licence (LGPL).
A legal expert system is a domain-specific expert system that uses artificial intelligence to emulate the decision-making abilities of a human expert in the field of law. Legal expert systems employ a rule base or knowledge base and an inference engine to accumulate, reference and produce expert knowledge on specific subjects within the legal domain.
↑ Melioli, G.; Spenser, C.; Reggiardo, G.; Passalacqua, G.; Compalati, E.; Rogkakou, A.; Riccio, A. M.; Di Leo, E.; Nettis, E.; Canonica, G. W. (2014), Giovanni Melioli; Clive Spenser; Giorgio Reggiard; Giovanni Passalacqua; Enrico Compalati; Anthi Rogkakou; Anna Maria Riccio; Elisabetta Di Leo; Eustachio Nettis; Giorgio Walter Canonica (eds.), "Allergenius, an expert system for the interpretation of allergen microarray results", The World Allergy Organization Journal, 7 (1): 15, doi:10.1186/1939-4551-7-15, PMC4070085, PMID24995073
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