b. ross cosc 4f79 1 commercial tools size of system: –small systems 400 rules single user, pc...

B. Ross Cosc 4f79 1

Commercial tools

• Size of system:

– small systems• 400 rules• single user, PC based

– larger systems• narrow, problem-type specific or hybrid shells using many

problem-solving paradigms (rules, induction, NN, GA, ...)• 1000+ rules• can be multi-user (esp. WWW)

• Type of system

– expert system consultation

– decision-support system: high-end analysis of data (data mining)

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Commercial Tools

p.93-95

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Commercial Tools

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Commercial Tools

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Commercial Tools

• Evaluating knowledge engineering tools

- Consultation paradigm: diagnosis? planning? configuration?...

- AI paradigms: Representation, inference, control, uncertainty, neural nets

- Implementation: Lisp, Prolog, C based, speed, transportable, interfacing,compiled code, WWW

- User interface: explanation, graphics, windowing, knowledge engineering, - Applications: what applications have been implemented with the system

- Support: documentation, training, support services

Contemporary shells:

- multi-paradigm, PC-based (and up), integrate with std languages and applications (eg. databases)

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M.1

• by Tecknowledge Inc.

• prototyping tool

• can handle small systems (100-200 rule systems)

• implemented in Prolog

• EMYCIN strategy: backchaining with uncertainty, unknown values

• supports "variable" rules: rule macro's

• window, menu interface

• M4: latest version ($1000)- embeds expert system code into applications- VB version embeds into Visual Basic ($199)

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M.1

p. 107

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Flex

• Bundled expert system toolkit with Quintus Prolog, Macprolog, others

• multiple paradigms: forward and backward chaining, frames

• forward-chaining rule selection is flexible, and permits builtin or user-defined algorithms to be used

• Can use Prolog's inference engine: directly call prolog code

• "data-driven" programming: frame demons

• procedural control

• Macintosh interface primitives

• fairly rudimentary explanation: must indicate explicitly which rules can be in explanation -- and explanation is text (hybrid systems mean that explanation is a problem)

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Flex

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OPS5, OPS83

OPS5:

•Carnegie-Mellon•Used to implement XCON•Production-rule, forward-chaining system•Uses time stamps to fire rules (least-recently used strategy)•intended for larger expert systems•Implemented in Lisp•interface permits a programming environment

OPS83:

•successor to OPS5•more generalized rule format, control•embeddable in C


OPS5

p.118


RuleMaster

• by Radian Corporation (Texas) and Intelligent Terminals (Scotland)

• inductive inference system, intended for small to moderate systems

• modular approach: expert system components encoded in modules (procedures), which hierarchically call one another

• Can create rules usig ID3 algorithm, or encode if-then rules directly

• runs on unix or PC-DOS,

• down-compiles into C or FORTRAN if desired

• spreadsheet interface for creating example sets

• example systems: Willard (severe storm forecasting), OIL (oil tank diagnosis)


ART

• The Automated Reasoning Tool (by Inference Corporation; now owned by Brightware Inc))

• hybrid tool kit for knowledge system development • 4 components: - knowledge language - compiler (knowledge language --> Lisp) - applier (inference engine) - development environment

• Uses a number of inference paradigms, including frames, logical represenations, forward and backward chaining, procedural execution, uncertainty

• systems range from $8000-$150,000


ART

p.122


Intellicorp

KEE: Knowledge Engineering Environment by IntelliCorp

• hybrid system, used for number of genetic expert systems

• uses frames, rules, procedures, backward and forward chaining

• $60,000 in 1985 (today’s price ???)

Kappa-PC: PC Windows shell

• object-oriented, rule-based GUI environment

• interface builder

• $995


KEE

p. 124


Trends for commercial shells

• Most run on PC’s or distributed networks of PC’s• WWW is a hot area! Web is now a standard interface for production expert

systems.• Java is becoming an implementation language• Highly interactive development environment are the norm• Most systems include a library of various tools & technologies

– forward & backward rules, rule induction, NN’s, fuzzy, GA’s• The difference between decision support environments and expert

systems is becoming vague– data mining applications use same tools as expert systems, although

they are applied for often different purposes– main dogmatic difference: expert system KB needs human expert,

while data mining uses auto techniques on large DB – both are merging for some problem domains

• New AI technologies will find their way into shells

b. ross cosc 4f79 1 commercial tools size of system: –small systems 400 rules single user, pc...

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