Xcon

Last updated

The R1 (internally called XCON, for eXpert CONfigurer) program was a production-rule-based system written in OPS5 by John P. McDermott of Carnegie Mellon University in 1978 to assist in the ordering of DEC's VAX computer systems by automatically selecting the computer system components based on the customer's requirements.

Contents

Overview

In developing the system, McDermott made use of experts from both DEC's PDP/11 and VAX computer systems groups. These experts sometimes even disagreed amongst themselves as to an optimal configuration. The resultant "sorting it out" had an additional benefit in terms of the quality of VAX systems delivered.

XCON first went into use in 1980 in DEC's plant in Salem, New Hampshire. It eventually had about 2500 rules. By 1986, it had processed 80,000 orders, and achieved 95–98% accuracy. It was estimated to be saving DEC $25M a year by reducing the need to give customers free components when technicians made errors, by speeding the assembly process, and by increasing customer satisfaction.

Before XCON, when ordering a VAX from DEC, every cable, connection, and bit of software had to be ordered separately. (Computers and peripherals were not sold complete in boxes as they are today.) The sales people were not always very technically expert, so customers would find that they had hardware without the correct cables, printers without the correct drivers, a processor without the correct language chip, and so on. This meant delays and caused a lot of customer dissatisfaction and resultant legal action. XCON interacted with the sales person, asking critical questions before printing out a coherent and workable system specification/order slip.

XCON's success led DEC to rewrite XCON as XSEL—a version of XCON intended for use by DEC's salesforce to aid a customer in properly configuring their VAX (so they would not, say, choose a computer too large to fit through their doorway or choose too few cabinets for the components to fit in). Location problems and configuration were handled by yet another expert system, XSITE.

McDermott's 1980 paper [1] on R1 won the AAAI Classic Paper Award in 1999. Legendarily, the name of R1 comes from McDermott, who supposedly said as he was writing it, "Three years ago I couldn't spell knowledge engineer, now I are one."

See also

Related Research Articles

<span class="mw-page-title-main">Expert system</span> Computer system emulating the decision-making ability of a human expert

In artificial intelligence, 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 code. The first expert systems were created in the 1970s and then proliferated in the 1980s. Expert systems were among the first truly successful forms of artificial intelligence (AI) software. An expert system is divided into two subsystems: the inference engine and the knowledge base. The knowledge base represents facts and rules. The inference engine applies the rules to the known facts to deduce new facts. Inference engines can also include explanation and debugging abilities.

<span class="mw-page-title-main">VAX</span> Line of computers sold by Digital Equipment Corporation

VAX is a series of computers featuring a 32-bit instruction set architecture (ISA) and virtual memory that was developed and sold by Digital Equipment Corporation (DEC) in the late 20th century. The VAX-11/780, introduced October 25, 1977, was the first of a range of popular and influential computers implementing the VAX ISA. The VAX family was a huge success for DEC, with the last members arriving in the early 1990s. The VAX was succeeded by the DEC Alpha, which included several features from VAX machines to make porting from the VAX easier.

<span class="mw-page-title-main">Symbolic artificial intelligence</span> Methods in artificial intelligence research

In artificial intelligence, symbolic artificial intelligence is the term for the collection of all methods in artificial intelligence research that are based on high-level symbolic (human-readable) representations of problems, logic and search. Symbolic AI used tools such as logic programming, production rules, semantic nets and frames, and it developed applications such as knowledge-based systems, symbolic mathematics, automated theorem provers, ontologies, the semantic web, and automated planning and scheduling systems. The Symbolic AI paradigm led to seminal ideas in search, symbolic programming languages, agents, multi-agent systems, the semantic web, and the strengths and limitations of formal knowledge and reasoning systems.

Computer-aided maintenance refers to systems that utilize software to organize planning, scheduling, and support of maintenance and repair. A common application of such systems is the maintenance of computers, either hardware or software, themselves. It can also apply to the maintenance of other complex systems that require periodic maintenance, such as reminding operators that preventive maintenance is due or even predicting when such maintenance should be performed based on recorded past experience.

Electronic data processing (EDP) can refer to the use of automated methods to process commercial data. Typically, this uses relatively simple, repetitive activities to process large volumes of similar information. For example: stock updates applied to an inventory, banking transactions applied to account and customer master files, booking and ticketing transactions to an airline's reservation system, billing for utility services. The modifier "electronic" or "automatic" was used with "data processing" (DP), especially c. 1960, to distinguish human clerical data processing from that done by computer.

OPS5 is a rule-based or production system computer language, notable as the first such language to be used in a successful expert system, the R1/XCON system used to configure VAX computers.

Charles L. Forgy is an American computer scientist, known for developing the Rete algorithm used in his OPS5 and other production system languages used to build expert systems.

<span class="mw-page-title-main">DEC PRISM</span> RISC instruction set architecture

PRISM was a 32-bit RISC instruction set architecture (ISA) developed by Digital Equipment Corporation (DEC). It was the outcome of a number of DEC research projects from the 1982–1985 time-frame, and the project was subject to continually changing requirements and planned uses that delayed its introduction. This process eventually decided to use the design for a new line of Unix workstations. The arithmetic logic unit (ALU) of the microPrism version had completed design in April 1988 and samples were fabricated, but the design of other components like the floating point unit (FPU) and memory management unit (MMU) were still not complete in the summer when DEC management decided to cancel the project in favor of MIPS-based systems. An operating system codenamed MICA was developed for the PRISM architecture, which would have served as a replacement for both VAX/VMS and ULTRIX on PRISM.

<span class="mw-page-title-main">VAXBI bus</span>

The VAXBI bus is a computer bus designed and sold by the Digital Equipment Corporation (DEC) of Maynard, Massachusetts.

Cincom Systems, Inc., is a privately held multinational computer technology corporation founded in 1968 by Tom Nies, Tom Richley, and Claude Bogardus.

<span class="mw-page-title-main">MicroVAX</span> Family of low-cost minicomputers

The MicroVAX is a discontinued family of low-cost minicomputers developed and manufactured by Digital Equipment Corporation (DEC). The first model, the MicroVAX I, was introduced in 1983. They used processors that implemented the VAX instruction set architecture (ISA) and were succeeded by the VAX 4000. Many members of the MicroVAX family had corresponding VAXstation variants, which primarily differ by the addition of graphics hardware. The MicroVAX family supports Digital's VMS and ULTRIX operating systems. Prior to VMS V5.0, MicroVAX hardware required a dedicated version of VMS named MicroVMS.

Configurators, also known as choice boards, design systems, toolkits, or co-design platforms, are responsible for guiding the user through the configuration process. Different variations are represented, visualized, assessed and priced which starts a learning-by-doing process for the user. While the term “configurator” or “configuration system” is quoted rather often in literature, it is used for the most part in a technical sense, addressing a software tool. The success of such an interaction system is, however, not only defined by its technological capabilities, but also by its integration in the whole sale environment, its ability to allow for learning by doing, to provide experience and process satisfaction, and its integration into the brand concept.

Drew McDermott was a professor of Computer Science at Yale University. He was known for his contributions in artificial intelligence and automated planning.

The VAX 9000 is a discontinued family of mainframes developed and manufactured by Digital Equipment Corporation (DEC) using custom ECL-based processors implementing the VAX instruction set architecture (ISA). Equipped with optional vector processors, they were marketed into the supercomputer space as well. As with other VAX systems, they were sold with either the VMS or Ultrix operating systems.

The VAXft was a family of fault-tolerant minicomputers developed and manufactured by Digital Equipment Corporation (DEC) using processors implementing the VAX instruction set architecture (ISA). "VAXft" stood for "Virtual Address Extension, fault tolerant". These systems ran the OpenVMS operating system, and were first supported by VMS 5.4. Two layered software products, VAXft System Services and VMS Volume Shadowing, were required to support the fault-tolerant features of the VAXft and for the redundancy of data stored on hard disk drives.

The Digital Storage Systems Interconnect (DSSI) is a computer bus developed by Digital Equipment Corporation for connecting storage devices and clustering VAX systems. It was designed as a smaller and lower-cost replacement for the earlier DEC Computer Interconnect that would be more suitable for use in office environments. DSSI was superseded by Parallel SCSI.

Knowledge-based configuration, also referred to as product configuration or product customization, is an activity of customising a product to meet the needs of a particular customer. The product in question may consist of mechanical parts, services, and software. Knowledge-based configuration is a major application area for artificial intelligence (AI), and it is based on modelling of the configurations in a manner that allows the utilisation of AI techniques for searching for a valid configuration to meet the needs of a particular customer.

A VMScluster, originally known as a VAXcluster, is a computer cluster involving a group of computers running the OpenVMS operating system. Whereas tightly coupled multiprocessor systems run a single copy of the operating system, a VMScluster is loosely coupled: each machine runs its own copy of OpenVMS, but the disk storage, lock manager, and security domain are all cluster-wide, providing a single system image abstraction. Machines can join or leave a VMScluster without affecting the rest of the cluster. For enhanced availability, VMSclusters support the use of dual-ported disks connected to two machines or storage controllers simultaneously.

Configuration Lifecycle Management (CLM) is the management of all product configuration definitions and configurations across all involved business processes applied throughout the lifecycle of a product.

Systime Computers Ltd was a British computer manufacturer and systems integrator of the 1970s and 1980s. During the late 1970s and early 1980s, Systime become the second largest British manufacturer of computers, specializing in the minicomputer market.

References

  1. McDermott, John (1980). "R1: An Expert in the Computer Systems Domain" (PDF). Proceedings of the First AAAI Conference on Artificial Intelligence. AAAI'80. Stanford, California: AAAI Press: 269–271. Archived from the original (PDF) on 2017-11-16.