Cover Page Uploaded June 27, 2011 The Hunt for New Abstractions Author: Jeffrey G. Long ([email protected]) 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.
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Subsymbolic: neither syntax nor semantics, e.g. natural systems
September 28, 2001 Copyright 2001 Jeff Long 2
We may have competence in using certain kinds of y p gcomplex 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 butThis is not because of the nature of the systems, but rather because our notational systems – our abstractions -- are inadequate
Complexity is not a property of systems; rather, perplexity is a property of the observer
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These problems cannot be solved by working harderThese problems cannot be solved by working 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-defeatingp y g
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Each primary notational system maps a different “abstraction space” Abstraction spaces are incommensurable Perceiving these is a unique human ability 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 seeAcquiring literacy in a notation is learning how to see a new abstraction space
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So Far We Have Settled Maybey12 Major Abstraction Spaces
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All higher forms of thinking require the use of one or g g qmore 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 acquireour 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
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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
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Current Analysis Methods Work Only Under Certain Conditions
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Rules are a Broader Way of Describing Things
Multi-notational: can include all other notational systems
E li itl ti tExplicitly contingent
Describe both behavior and mechanismDescribe both behavior and mechanism
Thousands or millions can be assembled and acted upon by computer
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And Complex Rules Can be Stored asAnd 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
F ti l t t ti fFocuses on optimal computer representation of complex, conditional and changing rules
Based on a new abstraction called ruleforms
The breakthrough was to find the unchanging features of changing systems
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The Theory Offers a Different Way to L k C l S d PLook at Complex Systems and Processes
location In Hindu-Arabic numerals, this is column position In ruleforms this is column position In ruleforms, this is column position
Thousands of rules can fit in same ruleformThere are multiple basic ruleforms, not just one But the total number is still small (<100?)
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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
“A i ti ” ft h littl k l d f“Animation” software has little or no knowledge of the external world
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This Creates New Levels for Analysis yand Representation
Standard Terminology (if any) Ultra-Structure Instance Ultra-Structure Level U-S ImplementationStandard Terminology (if any) Ultra-Structure Instance Name
Ultra-Structure Level Name
U-S Implementation
behavior, physical entities and relationships, processes
particular(s) surface structure system behavior
rules, laws, constraints, guidelines, rules of thumb
rule(s) middle structure data and some software (animation procedures)
(no standard or common term)
ruleform(s) deep structure tables
(no standard or common universal(s) sub-structure attributes, fieldsterm)
tokens, signs or symbols token(s) notational structure character set
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The Ruleform HypothesisComplex system structures are created by not-
il l d thnecessarily complex processes; and these processes are created by the animation of operating rules. Operating rules can be grouped i ll b f l h f iinto a small number of classes whose form is prescribed by "ruleforms". While the operating rules of a system change over time, the ruleforms
i ll d i d ll i fremain constant. A well-designed collection of ruleforms can anticipate all logically possible operating rules that might apply to the system,
d h d f hand constitutes the deep structure of the system.
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The CoRE HypothesisWe can create “Competency Rule Engines”, or C RE i ti f 50 l f th tCoREs, consisting of <50 ruleforms, that are sufficient to represent all rules found among systems sharing broad family resemblances, e.g. all
ti Th i d fi iti d t t ill bcorporations. Their definitive deep structure will be permanent, unchanging, and robust for all members of the family, whose differences in manifest
d b h i ill b d i lstructures and behaviors will 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.
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The Deep Structure of a System p ySpecifies 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?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,If we can answer these questions about a system, then we have achieved real understanding
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Suggestion 1
To advance our mental capabilities as a species, and to address the problems we currently face as a civilization we must systematically and comparativelycivilization, we must systematically and comparatively study notational systems to create wholly new abstractions and thereby revolutionary new notational s stemsnotational systems.
This is the goal of notational engineeringThis is the goal of notational engineering.
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Suggestion 2
One example of a new abstraction is ruleforms ToOne example of a new abstraction is ruleforms. To 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.
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ReferencesLong, J., and Denning, D., “Ultra-Structure: A design theory for
l d ” C i i f hcomplex systems and processes.” In Communications of the ACM (January 1995)Long, J., “Representing emergence with rules: The limits of addition ” In Lasker G E and Farre G L (editors) Advancesaddition. In Lasker, G. E. and Farre, G. L. (editors), Advances in Synergetics, Volume I: Systems Research on Emergence. (1996)Long, J., “A new notation for representing business and other g, , p grules.” 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. ( t dit ) S i ti S i l I N t ti l E i i(guest editor), Semiotica Special Issue: Notational Engineering, Volume 125-1/3 (1999)