The hunt for new abstractions
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The document presents a talk by Jeffrey G. Long on the need for new notational systems to understand complex systems more effectively, advocating for the field of 'notational engineering.' It introduces the concept of 'ultra-structure theory,' which proposes a way to represent knowledge and rules of complex systems using a new abstraction called 'ruleforms.' The primary thesis is that many contemporary problems stem from inadequate notational systems, and solutions can emerge from a systematic study of diverse notational forms.
The hunt for new abstractions
- 1. Cover Page The Hunt for New Abstractions Author: Jeffrey G. Long (jefflong@aol.com) Date: September 28, 2001 Forum: Talk presented at the University of Utah. Contents Pages 1‐2: Proposal and Bio Pages 3‐24: Slides intermixed with 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 Hunt for New Abstractions: Notational Engineering and Ultra- Structure Jeffrey G. Long September 28, 2001 jefflong@aol.com j ffl @ l
- 5. We Have Never Really Studied Notational Systems per se All systems can be categorized into four types: y g yp Formal: syntax only, e.g. formal logic, formal language theory, pure mathematics Informal: semantics only, e.g. art, advertising, politics, religious symbols Notational: both syntax and semantics, e g semantics e.g. natural language, musical notation, money, cartography Subsymbolic: neither syntax nor semantics, e.g. natural systems September 28, 2001 Copyright 2001 Jeff Long 2
- 6. We may have competence in using certain kinds of y p g complex systems but we still don’t understand them climate and weather economics, finance, markets , , medicine, physiology, biology, ecology This is not because of the nature of the systems but systems, rather because our notational systems – our abstractions -- are inadequate Complexity is not a property of systems; rather, perplexity is a property of the observer September 28, 2001 Copyright 2001 Jeff Long 3
- 7. These problems cannot be solved by working harder, harder using faster computers, or moving to OO techniques Many if not most problems today are fundamentally representational in character Using the wrong, or too-limited, a notational system is inescapably self-defeating p y g September 28, 2001 Copyright 2001 Jeff Long 4
- 8. Each primary notational system maps a different “abstraction space” Abstraction spaces are incommensurable Perceiving these is a unique human ability Abstraction spaces are discoveries, not inventions Abstraction spaces are real Acquiring literacy in a notation is learning how to see a new abstraction space September 28, 2001 Copyright 2001 Jeff Long 5
- 9. So Far We Have Settled Maybe y 12 Major Abstraction Spaces September 28, 2001 Copyright 2001 Jeff Long 6
- 10. All higher forms of thinking require the use of one or g g q more notational systems The notational systems we habitually use influence the manner in which we perceive our environment: our picture of the universe shifts as we acquire literacy in new notational systems Notational systems have been central to the evolution of the modern mind and modern civilization September 28, 2001 Copyright 2001 Jeff Long 7
- 11. Every notational system has limitations: a y y “complexity barrier” The problems we face now as a civilization are, in many cases, notational We need a more systematic way to develop and settle abstraction spaces: notational engineering September 28, 2001 Copyright 2001 Jeff Long 8
- 12. Current Analysis Methods Work Only Under Certain Conditions September 28, 2001 Copyright 2001 Jeff Long 9
- 13. Rules are a Broader Way of Describing Things Multi-notational: can include all other notational systems Explicitly E li itl contingent ti t Describe both behavior and mechanism Thousands or millions can be assembled and acted upon by computer September 28, 2001 Copyright 2001 Jeff Long 10
- 14. And Complex Rules Can be Stored as Data in a Relational Database Ultra-Structure Theory is a general theory of systems representation, developed/tested starting 1985 Focuses on optimal computer representation of F ti l t t ti f complex, conditional and changing rules Based on a new abstraction called ruleforms The breakthrough was to find the unchanging features of changing systems September 28, 2001 Copyright 2001 Jeff Long 11
- 15. The Theory Offers a Different Way to Look L k at Complex S C l Systems and Pd Processes observable behaviors surface structure generates rules middle structure constrains form of rules f f l deep structure September 28, 2001 Copyright 2001 Jeff Long 12
- 16. Hypothesis: Any Type of Statement Can yp y yp Be Reformulated into an If-Then Rule Natural language statements Musical scores Logical arguments Business processes Architectural drawings Mathematical statements September 28, 2001 Copyright 2001 Jeff Long 13
- 17. Rules Can be Represented in Place-Value (Tabular) Form Place value assigns meaning based on content and location In Hindu-Arabic numerals, this is column position In ruleforms, this is column position ruleforms Thousands of rules can fit in same ruleform There are multiple basic ruleforms, not just one But the total number is still small (<100?) September 28, 2001 Copyright 2001 Jeff Long 14
- 18. Structured and Ultra-Structured Data are 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 small software engine to reason with them using standard deductive logic “Animation” ft “A i ti ” software h littl or no knowledge of has little k l d f the external world September 28, 2001 Copyright 2001 Jeff Long 15
- 19. This Creates New Levels for Analysis y and Representation Standard Terminology (if any) Ultra-Structure Instance Ultra-Structure Level U-S Implementation Name Name behavior, physical entities particular(s) surface structure system behavior and relationships, processes rules, laws, constraints, rule(s) middle structure data and some guidelines, rules of thumb software (animation procedures) (no standard or common ruleform(s) deep structure tables term) (no standard or common universal(s) sub-structure attributes, fields term) tokens, signs or symbols token(s) notational structure character set September 28, 2001 Copyright 2001 Jeff Long 16
- 20. The Ruleform Hypothesis Complex system structures are created by not- necessarily complex processes; and these il l d th 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 i ll d i d ll i f ruleforms can anticipate all logically possible operating rules that might apply to the system, and constitutes the deep structure of the system. d h d f h September 28, 2001 Copyright 2001 Jeff Long 17
- 21. The CoRE Hypothesis 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. Their definitive d ti Th i d fi iti deep structure will b t t ill be permanent, unchanging, and robust for all members of the family, whose differences in manifest structures and b h i d behaviors will b represented entirely ill be d i l 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 28, 2001 Copyright 2001 Jeff Long 18
- 22. The Deep Structure of a System p y 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 28, 2001 Copyright 2001 Jeff Long 19
- 23. Suggestion 1 To advance our mental capabilities as a species, and to address the problems we currently face as a civilization, civilization we must systematically and comparatively study notational systems to create wholly new abstractions and thereby revolutionary new notational systems. s stems This is the goal of notational engineering. engineering September 28, 2001 Copyright 2001 Jeff Long 20
- 24. Suggestion 2 One example of a new abstraction is ruleforms To ruleforms. truly understand complex systems, we must get beyond appearances (surface structure) and rules (middle structure) to the ruleforms (deep structure) and beyond. This is the goal of Ultra-Structure Theory. September 28, 2001 Copyright 2001 Jeff Long 21
- 25. References Long, J., and Denning, D., “Ultra-Structure: A design theory for complex systems and processes.” In C l d ” Communications of the i i f h ACM (January 1995) Long, J., “Representing emergence with rules: The limits of addition. addition ” In Lasker, G E. and Farre G L (editors) Advances Lasker G. E Farre, G. L. (editors), in Synergetics, Volume I: Systems Research on Emergence. (1996) Long, J., “A new notation for representing business and other g, , p g rules.” In Long, J. (guest editor), Semiotica Special Issue: Notational Engineering, Volume 125-1/3 (1999) Long, J., “How could the notation be the limitation?” In Long, J. (guest editor), S i ti S ( t dit ) Semiotica Special Issue: Notational Engineering, i lI N t ti lE i i Volume 125-1/3 (1999) September 28, 2001 Copyright 2001 Jeff Long 22