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High Level Logic Concept Presentation Suggesting Higher Level Logic for Expert Systems Copyright © High Level Logic Concept Presentation Suggesting Higher Level Logic for Expert Systems Copyright © 2005 Roger F. Gay rogerfgay@yahoo. com HLL August, 2005 Roger F. Gay

Formulation of the ideas in this presentation began in 1986. The World is Catching Formulation of the ideas in this presentation began in 1986. The World is Catching Up! HLL August, 2005 Roger F. Gay

Past Proposals SBIR proposals for development of an HLL demonstration were submitted to NASA, Past Proposals SBIR proposals for development of an HLL demonstration were submitted to NASA, DARPA, and the NSF ~ 1990. Funding was not approved. HLL August, 2005 Roger F. Gay

Inspiration The proposals may have inspired DARPA Project Genoa, initially known as Collaborative Crisis Inspiration The proposals may have inspired DARPA Project Genoa, initially known as Collaborative Crisis Understanding and Mitigation. I did not participate in Genoa. I do not believe My HLL has been developed. HLL August, 2005 Roger F. Gay

Evolutionary Pressure HLL August, 2005 Roger F. Gay Evolutionary Pressure HLL August, 2005 Roger F. Gay

In 1986 Application oriented researchers became disenchanted with the limitations of rule-based technology, even In 1986 Application oriented researchers became disenchanted with the limitations of rule-based technology, even with meta-knowledge, objects, frames, and Lisp machines. HLL August, 2005 Roger F. Gay

EMYCIN Generation • Narrowly focused domains • Very difficult to integrate • No interprocess EMYCIN Generation • Narrowly focused domains • Very difficult to integrate • No interprocess communication (information exchange, multiple experts. . . ) • Rules! So what? HLL August, 2005 Roger F. Gay

Practical AI Artificial intelligence gets real. By Daniel Lyons. Forbes Global (November 30, 1998). Practical AI Artificial intelligence gets real. By Daniel Lyons. Forbes Global (November 30, 1998). "By contrast, Feigenbaum succeeded by thinking small. Unlike his rivals, he didn't set out to recreate all of human intelligence in a computer. His idea was to take a particular expert -- a chemist, an engineer, a pulmonary specialist -- and figure out how that person solved a single narrow problem. Then he encoded that person's problemsolving method into a set of rules that could be stored in a computer. " HLL August, 2005 Roger F. Gay

AI Evolution Develop unconventional software applications that require symbolic representation and reasoning that humans AI Evolution Develop unconventional software applications that require symbolic representation and reasoning that humans currently do better than machines. Separate general structure and logic from domain specific knowledge. HLL August, 2005 Roger F. Gay

Modern Technolgy • Internet • XML, SOAP, etc. • Rule engines and OO programs Modern Technolgy • Internet • XML, SOAP, etc. • Rule engines and OO programs • Intelligent Agents HLL August, 2005 Roger F. Gay

High Level Logic for Expert Systems Think Just a Little Higher Think Just a High Level Logic for Expert Systems Think Just a Little Higher Think Just a Little Bigger The stage is set for a revolution. HLL August, 2005 Roger F. Gay

Organizational Context Intelligence is all about acting in context; adapting to an environment, meeting Organizational Context Intelligence is all about acting in context; adapting to an environment, meeting basic needs, responding to threats, living with other humans, participating in organized activities. Intelligence is a product of the context that shaped it. HLL August, 2005 Roger F. Gay

Executive Role • Define Goals • Provide Strategy • Assign Authority & Responsibility • Executive Role • Define Goals • Provide Strategy • Assign Authority & Responsibility • Assess Overall Results • HL Corporate Relationships HLL August, 2005 Roger F. Gay

Manager’s HLL • Collect Information • Define a Problem or Opportunity • Assign Tasks Manager’s HLL • Collect Information • Define a Problem or Opportunity • Assign Tasks • Coordinate Activities • Finalize / Approve Decisions HLL August, 2005 Roger F. Gay

Expert’s HLL • Refine Problem Definition • Assemble Detailed Information • Perform Analysis • Expert’s HLL • Refine Problem Definition • Assemble Detailed Information • Perform Analysis • Identify Alternatives • Recommend Solutions HLL August, 2005 Roger F. Gay

Drones Perform specialized tasks: Examples: • Industrial Robots • Mission Programmable Weapons HLL August, Drones Perform specialized tasks: Examples: • Industrial Robots • Mission Programmable Weapons HLL August, 2005 Roger F. Gay

Long-Term Goals Large-scale, fully automated, real -time, “corporate” systems. Searchable, sharable, “cooperating” components from Long-Term Goals Large-scale, fully automated, real -time, “corporate” systems. Searchable, sharable, “cooperating” components from a variety of sources. HLL August, 2005 Roger F. Gay

Initial Expectations • Medium Scope (An Application) • Highly Integrated • Internet Communications • Initial Expectations • Medium Scope (An Application) • Highly Integrated • Internet Communications • Domain Specific Language (XML) • Focus on Experts HLL August, 2005 Roger F. Gay

Why Focus on Experts? • Executives Need Corporate Capabilities • Managers Need Subordinates • Why Focus on Experts? • Executives Need Corporate Capabilities • Managers Need Subordinates • Drones “aren’t paid to think. ” • Experts can collaborate HLL August, 2005 Roger F. Gay

Component Technology 1. Define the Problem 2. Collect Information 3. Perform Analysis 4. Identify Component Technology 1. Define the Problem 2. Collect Information 3. Perform Analysis 4. Identify Alternative Solutions 5. Recommend a Solution HLL August, 2005 Roger F. Gay

Recursive Slightly Generic Example: • Define a problem • Collect Information – Which analysis Recursive Slightly Generic Example: • Define a problem • Collect Information – Which analysis should be used? – What information is needed? • Perform Analysis – Interpreting input? – How should the output be presented? HLL August, 2005 Roger F. Gay

A Simple Start HLL August, 2005 Roger F. Gay A Simple Start HLL August, 2005 Roger F. Gay

Define a Problem Identify the type of problem from the choice of subject experts Define a Problem Identify the type of problem from the choice of subject experts currently available using a rule-based expert system. HLL August, 2005 Roger F. Gay

Define a Problem: Examples General consultant on soil-water decides whethere is a drainage, irrigation, Define a Problem: Examples General consultant on soil-water decides whethere is a drainage, irrigation, or nutrient problem. Ship board defense system consults with aircraft identification sub-system to decide whether to choose com. protocol or perform threat assessment. HLL August, 2005 Roger F. Gay

Collect Information Suggest stored data and data generated by system components are exchanged in Collect Information Suggest stored data and data generated by system components are exchanged in XML. To visually demonstrate this step, an example might include user input using an NL Menu system. HLL August, 2005 Roger F. Gay

Collect Information: Examples Drainage Problem: Need detailed information on soil type, slopes, and water Collect Information: Examples Drainage Problem: Need detailed information on soil type, slopes, and water volume. Threat Assessment: Aircraft type, flight vector, and nationality. HLL August, 2005 Roger F. Gay

Perform Analysis This component should support use of whatever analytical software is needed by Perform Analysis This component should support use of whatever analytical software is needed by the application. Analysis software needs to take set-up data from the HLL system and the HLL system needs to make use of results. HLL August, 2005 Roger F. Gay

Identify Alternatives Match detailed problem characteristics with alternative solutions. HLL August, 2005 Roger F. Identify Alternatives Match detailed problem characteristics with alternative solutions. HLL August, 2005 Roger F. Gay

Identify Alternatives: Examples Drainage Problem: Alter slopes, modify irrigation schedule, or sell the farm. Identify Alternatives: Examples Drainage Problem: Alter slopes, modify irrigation schedule, or sell the farm. Threat Response: Hail the pilot, call the President, fire a warning shot, or shoot to kill. HLL August, 2005 Roger F. Gay

Recursion: Example An alternative solution to the drainage problem is to modify the irrigation Recursion: Example An alternative solution to the drainage problem is to modify the irrigation schedule. Irrigation is a “problem type” in the general soil-water consultant’s knowledge base. The generalist can have a consultation with the irrigation specialist before recommending a drainage solution. HLL August, 2005 Roger F. Gay

Recursion We can reuse the general flow of logic for sub-problems and sub-problems of Recursion We can reuse the general flow of logic for sub-problems and sub-problems of subproblems; compartmentalizing specialized expertise; facilitating reuse of knowledge. Easier to build complex “thinking” systems. HLL August, 2005 Roger F. Gay

Recommendations Traditional role of rule-based expert systems. HLL August, 2005 Roger F. Gay Recommendations Traditional role of rule-based expert systems. HLL August, 2005 Roger F. Gay

Simple Start: Is it of value? • Design HLL for Experts • Prototype HLL Simple Start: Is it of value? • Design HLL for Experts • Prototype HLL Engine and Development Tools • Wide Range of Applications • A Step Toward Long-Term Goals HLL August, 2005 Roger F. Gay

The Future in Space The intelligent space station has a responsibility to maintain its The Future in Space The intelligent space station has a responsibility to maintain its orbit and protect itself and its contents – including humans. The maintenance manager (software) is informed of a change in resistance in the outer hull and sends a maintenance drone to look it over. The drone returns imagary and measurements to the manager who consults with specialized experts. The drone is ordered to perform repairs. HLL August, 2005 Roger F. Gay

The Future in Agriculture The farm manager (software) is informed of a change in The Future in Agriculture The farm manager (software) is informed of a change in the average reflectance of soybean crop leaves. It consults with a weather specialist and then initiates soil-water measurements. After consulting with specialists in irrigation and agricultural economics, it adjusts the short-term irrigation schedule to maximize profit. HLL August, 2005 Roger F. Gay

The Future Battlefield The battle manager (software) makes field assessments, defines targets, and orders The Future Battlefield The battle manager (software) makes field assessments, defines targets, and orders drones to attack. It regularly consults with specialized experts to determine the choices that will best implement a defined strategy. Outcomes are returned to an executive (software) that compares battle status to expectations and alters strategy accordingly. HLL August, 2005 Roger F. Gay

The Future Consultant HLL applications with the addition of stored commentary that fills out The Future Consultant HLL applications with the addition of stored commentary that fills out written reports in “standard HLL form” explaining the problem, providing detailed information, analytical results, alternatives, and recommendations. HLL August, 2005 Roger F. Gay

The Future Divorce Court The “judge” (software) collects detailed information, uses a specialist to The Future Divorce Court The “judge” (software) collects detailed information, uses a specialist to set standard of living goals for parents and children and to find the sound mathematically balance between spousal and child support; issues a written order and informs payment tracking systems. HLL August, 2005 Roger F. Gay