International Cognitive Computing

  Welcome to:

International Cognitive Computing

and

 CAMBO a multi-Expert System Generator.

Nicholas J. Zendelbach

International Cognitive Computing is a research and design company, developing computer systems that allow employees of a company to easily transfer their individual business knowledge (rules), about how they conduct business, to a computer and share in the collective knowledge of all employees. ICC consulting services install the copyrighted product CAMBO©, containing the methodology, techniques and tools for a multi-EXPERT system©.

SEE VIDEO CLIPS.

Research at Jet Propulsion Laboratory (JPL)

Automated Problem Solving Group

Jet Propulsion Laboratory

4800 Oak Grove Dr.

Pasadena, California 91109

A CAMBO R&D Milestone.

CAMBO R&D Contributing Design.

(CAMBO: a multi-Expert System integrates the knowledge of all SMEs', 'manner in which they conduct business'. (Rules))

A general-purpose planner called DEVISER has been implemented which correctly accounts for time. Thus it has a capability for scheduling actions. The initial application has been to generate commands for the on-board spacecraft computer of the VOYAGER mission. This code generation, till now, has been done by a team of programmers responding to requests from scientists. The performance of DEVISER in generating code to meet similar requests was impressive enough to cause the VOYAGER spacecraft project to form a users group to write knowledge bases that would exploit the capabilities of DEVISER. This group, which has almost no knowledge of the internal workings of DEVISER, has been successfully expanding the knowledge base to form a model of VOYAGER activities. Various improvements requested by them have been incorporated in DEVISER. The VOYAGER mission also organized another group that has constructed the intelligent work station interface. VOYAGER plans to use DEVISER during its encounter with Uranus.

A general-purpose diagnostician, FAITH, has been implemented with an initial application to monitoring VOYAGER (and other spacecraft) telemetry. Detection and diagnosis of errors is a major activity of mission operations that FAITH is well suited to handle. Both FAITH and DEVISER are predicate logic systems with “natural” knowledge base representations. FAITH represents declarative knowledge in essentially a frame format which the system expands into logical assertions as required. Much of the declarative representation is, in effect, a substitute for a combined system and circuit diagram. The remainder of the declarative knowledge is a natural representation of problem knowledge, similar to the hierarchy of diseases in medicine. Procedural knowledge is handled by productions. Universal modes of troubleshooting employed by humans have been modelled so that many productions are incorporated as permanent system features. The diagnostician also has a special interface package, an Execution Monitor, to monitor the telemetry stream for errorsand to generate alarms.

R&D: Dr. Steven Vere.

CAMBO

Methodology

Techniques

and

Tools.

Machine Learning

and

Natural Language Processing

       begin with

 Knowledge Normalization methodology.

Methodology

"Knowledge is a person's understanding of how the world around them operates"

Techniques

Any entity that can be described in "English Grammatical Sentences" can be extracted and software (Rule processing) managed through a Normalized Knowledge Base.

Tools.
 Knowledge Engineering

• Knowledge Normalization Methodology.
• Storyboards
• LIPS1.
• LIPS2.
• MECA.
• AION.
• ORACLE.
• SYBASE.
• others.

Wikipedia

the free encyclopedia

 An expert system is software that attempts to provide an answer to a problem, or clarify uncertainties where normally one or more human experts would need to be consulted. Expert systems are most common in a specific problem domain, and is a traditional application and/or subfield of artificial intelligence. A wide variety of methods can be used to simulate the performance of the expert however common to most or all are 1) the creation of a knowledge base which uses some knowledge representation formalism to capture the Subject Matter Expert's (SME) knowledge and 2) a process of gathering that knowledge from the SME and codifying it according to the formalism, which is called knowledge engineering. Expert systems may or may not have learning components but a third common element is that once the system is developed it is proven by being placed in the same real world problem solving situation as the human SME, typically as an aid to human workers or a supplement to some information system.