Notational engineering and the search for new intellectual primitives
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The document is a cover page for a presentation on Notational Engineering and the Search for New Intellectual Primitives. It includes the title, author, date, and location of the presentation. The contents section lists the proposal and bio on pages 1-2 and slides without text on pages 3-31. The document is licensed under a Creative Commons license.
Notational engineering and the search for new intellectual primitives
- 1. Cover Page Notational Engineering and the Search for New Intellectual Primitives Author: Jeffrey G. Long (jefflong@aol.com) Date: September 25, 2002 Forum: Talk presented at the Lawrence Livermore National Laboratory. Contents Pages 1‐2: Proposal and Bio Pages 3‐31: Slides (but no text) for presentation License This work is licensed under the Creative Commons Attribution‐NonCommercial 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by‐nc/3.0/ or send a letter to Creative Commons, 444 Castro Street, Suite 900, Mountain View, California, 94041, USA. Uploaded June 27, 2011
- 4. The Notation is the Limitation Notational Engineering and the Search for New Intellectual Primitives Jeffrey G. Long September 25, 2002 jefflong@aol.com
- 5. Proposed outline P d li 1: Background on the general problem: representation and notational systems 2: Overview of Ultra-Structure: an approach to complex systems using a new abstraction 3: Example: The Reviewers Assistance System September 25, 2002 Copyright 2002 Jeff Long 2
- 6. 1: The Problem September 25, 2002 Copyright 2002 Jeff Long 3
- 7. Many, if not most, of our current problems arise from y, , p the way we represent them We may have pragmatic competence in using certain kinds of complex systems but we still don’t really understand them theoretically – economics, finance, markets – medicine, physiology, biology, ecology This is not because of the nature of the systems, but rather because our analytical tools – our notational systems and the abstractions they reify -- are inadequate September 25, 2002 Copyright 2002 Jeff Long 4
- 8. Complexity is not a property of systems; rather, perplexity is a property of the observer Systems appear complex under certain conditions; when better understood they may still be “complicated” but they are tractable to explanation Using the wrong, or too-limited, an analytical toolset creates these “complexity barriers”; they cannot be breached without a new notational system b h d ih i l These problems cannot be solved by working harder, using faster computers, or moving to OO techniques; they do not arise due to lack of effort or lack of factual information September 25, 2002 Copyright 2002 Jeff Long 5
- 9. So far we have explored maybe 12 major abstraction spaces September 25, 2002 Copyright 2002 Jeff Long 6
- 10. Notational systems facilitate perception, cognition and communication Each primary notational system maps a different “abstraction space” – Abstraction spaces are incommensurable – Perceiving these is a uniquely human ability Acquiring literacy in a notation is learning how to see a new abstraction space Having acquired such literacy, we see the world differently and can think about it differently September 25, 2002 Copyright 2002 Jeff Long 7
- 11. Notational Theory Offers a New Intellectual Synthesis Broadened to include all notational systems (not just language), it sheds light on, and integrates: l ) i h d li h di – Whorf’s notion of linguistic relativity, – Chomsky’s notion of an innate linguistic capability y g p y – Toynbee’s notion of the evolution of civilizations by challenge and response – parts of numerous other theories in many areas September 25, 2002 Copyright 2002 Jeff Long 8
- 12. Conclusions From Section 1 Every set of intellectual primitives, reified in a y p , notational system, has limitations: these appear to us in the form of a “complexity barrier” Many of the problems we face now as a civilization a e u da e ta y ep ese tat o a o otat o a are fundamentally representational or notational We need a more systematic way to develop and settle abstraction spaces: notational engineering September 25, 2002 Copyright 2002 Jeff Long 9
- 13. 2: O New Approach 2 One N A h September 25, 2002 Copyright 2002 Jeff Long 10
- 14. Current engineering methods work well only under certain conditions September 25, 2002 Copyright 2002 Jeff Long 11
- 15. This is the area addressed by Ultra-Structure Theory Ultra-Structure Theory is a general theory of systems representation, developed/tested starting in 1985 F Focuses on optimal computer representation of complex, i l i f l conditional and changing rules Based on a new abstraction called ruleforms The breakthrough was to find the unchanging features of changing systems September 25, 2002 Copyright 2002 Jeff Long 12
- 16. Unfortunately, Unfortunately Complex and Changing Needs Exist in Every Organization Needs SW & DB time 1 time 2 time 3... September 25, 2002 Copyright 2002 Jeff Long 13
- 17. The theory is based upon a different way of describing complex systems and processes observable behaviors surface structure generates rules middle structure constrains form of rules f f l deep structure September 25, 2002 Copyright 2002 Jeff Long 14
- 18. As Wolfram has recently argued, rules are a very y g , y powerful way of describing things Multi-notational: can include all other notational systems Explicitly contingent Describe both behavior and mechanism H d d of th Hundreds f thousands can b represented and d be t d d executed by a desktop computer September 25, 2002 Copyright 2002 Jeff Long 15
- 19. Hypothesis: Any type of assertion can be reformulated into one or more If-Then rules Natural language statements Musical scores Logical arguments Business processes Architectural drawings Mathematical statements M th ti l t t t But often several “atomic” rules are needed to create atomic one “molecular” rule, e.g. “3 strikes and you’re out” September 25, 2002 Copyright 2002 Jeff Long 16
- 20. If/Then Rules are Best Represented as Data (records) Organized into Tables in a Relational Database O i d i t T bl i R l ti lD t b If A and B then consider C, D, E, F... A B C D E F 1 2 Rule # 3 4 5 } 1 Ruleform n September 25, 2002 Copyright 2002 Jeff Long 17
- 21. Structured and Ultra-Structured data are semantically y quite different Structured data separates algorithms and data, and is good for data processing and information retrieval tasks,e.g. reports, queries, data entry Ultra-Structured data has only “rules”, formatted in a manner that allows a very small inference engine to reason with them using standard deductive logic Th inference engine (“animation rules”) software The i f i (“ i i l ”) f has little or no knowledge of the external world September 25, 2002 Copyright 2002 Jeff Long 18
- 22. The Ruleform Hypothesis Complex system structures are created by not- necessarily complex processes; and these il l d h processes are created by the animation of operating rules. Operating rules can be grouped into a small number of classes whose form is i ll b f l h f i prescribed by "ruleforms". While the operating rules of a system change over time, the ruleforms remain constant. A well-designed collection of ruleforms can anticipate all logically possible operating rules that might apply to the system, and constitutes the deep structure of the system. September 25, 2002 Copyright 2002 Jeff Long 19
- 23. The CoRE Hypothesis Th C RE H th i We can create “Competency Rule Engines”, or CoREs, C RE consisting of <50 ruleforms, th t are i ti f 50 l f that sufficient to represent all rules found among systems sharing broad family resemblances, e.g. all corporations. Th i d fi iti d ll ti Their definitive deep structure t t will be permanent, unchanging, and robust for all members of the family, whose differences in manifest structures and b h i if d behaviors will b ill be represented entirely as differences in operating rules. The animation procedures for each engine will be relatively simple compared to current applications, requiring less than 100,000 lines of code in a third generation language. September 25, 2002 Copyright 2002 Jeff Long 20
- 24. The deep structure of a system specifies its ontology What is common among all systems of type X? What is the fundamental nature of type X systems? What are the primary processes and entities involved in type X systems? What makes systems of type X different from systems of type Y? If we can answer these questions about a system, then we have achieved real understanding September 25, 2002 Copyright 2002 Jeff Long 21
- 25. Conclusions From Section 2 One example of a new abstraction is ruleforms To ruleforms. truly understand complex systems such as biological systems, we must get beyond appearances (surface structure) and rules (middle structure) to the stable ruleforms (deep structure). This is the goal of Ultra-Structure Theory. September 25, 2002 Copyright 2002 Jeff Long 22
- 26. 3: Application Example: the Reviewer’s Assistance System September 25, 2002 Copyright 2002 Jeff Long 23
- 27. DOE Reviewer’s Assistance System Requirements 650 guides defining 65,000 topics that are or may be classified E Extensive background knowledge required to interpret i b k dk l d i d i guidance Guidance changes over time Terminology in documents changes over time The objective is advanced concept spotting, not document understanding September 25, 2002 Copyright 2002 Jeff Long 24
- 28. Normally This Would be Done Using an Expert System Shell ES often have trouble with >1,000 rules; RAS has >100,000 rules K i Key issue i the maintainability of rules by experts is h i i bili f l b There are many benefits from using relational database to store rules as data, including: – Built-in referential integrity – Easy report-writing and queries – S bj t experts can maintain knowledgebase directly, without Subject t i t i k l d b di tl ith t relying on KE or Programmers September 25, 2002 Copyright 2002 Jeff Long 25
- 29. RAS D fi Defines G id Guidance Concepts and All P C t d Possible ibl Lexical Expressions of Those Concepts System Define Convert Guides Interpretations Ready Read Apply Document Document Guidance Reviewed September 25, 2002 Copyright 2002 Jeff Long 26
- 30. Rules Specify Relations Between Topics, Concepts, and Tokens T k September 25, 2002 Copyright 2002 Jeff Long 27
- 31. Conclusions From Section 3 C l i F S i A rule-based system can provide precise and rigorous interpretation of key DOE terms and concepts A rule-based system stored as tables in a relational database allows creation of a knowledgebase which can become as large as necessary Such a knowledgebase is very easy to specify, change and review directly by subject experts September 25, 2002 Copyright 2002 Jeff Long 28
- 32. References Long, J., and Denning, D., “Ultra-Structure: A design theory for complex systems and processes.” In Communications of the ACM processes (January 1995) Long, J., “A new notation for representing business and other rules.” In Long, J. (guest editor), Semiotica Special Issue on Notational Engineering, Volume 125-1/3 (1999) Long, J., “How could the notation be the limitation?” In Long, J. (guest editor), Semiotica Special Issue on Notational Engineering, Volume 125-1/3 (1999) 125 1/3 Long, J., "Automated Identification of Sensitive Information in Documents Using Ultra-Structure". In Proceedings of the 20th Annual ASEM Conference, American Society for Engineering Management (October 1999) September 25, 2002 Copyright 2002 Jeff Long 29