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Representations and Compressions

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Representations and Compressions. Opportunity/Risk from Heuristic Shortcuts Michael Lissack Institute for the Study of Coherence and Emergence. “ Knowledge is not a matter of getting reality right, … but rather a matter of acquiring habits of action for coping with reality” - PowerPoint PPT Presentation
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Opportunity/Risk from Heuristic Shortcuts Michael Lissack Institute for the Study of Coherence and Emergence 1 Representations and Compressions
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Page 1: Representations and Compressions

Opportunity/Risk from Heuristic Shortcuts

Michael LissackInstitute for the Study of Coherence and Emergence

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Representations and Compressions

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“Knowledge is not a matter of getting reality right, … but rather a matter of acquiring habits of action for coping with reality”

Richard Rorty

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Representations

• The action or fact of one item standing for another.

• The substitution of an individual or class in place of another (indexicals)

Representations are labels and sign tokens of membership in a predefined category

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Compressions

• Compression is the reduction in size of data in order to save space or transmission time.

• Compressions can be either lossy {some information is permanently lost) or lossless (all information can be restored).

Compressions are stories, models, narratives whichallow the user to ask “what if”

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What is the Problem?

Models based on representations are concerned with reliable prediction

Models based on compressions are concerned with attaining better attunement with affordances

These goals are NOT the same

But all too often the models are confused7

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“Everything should be made as simple as possible.…But not simpler.

Albert Einstein

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Simple

ComplicatedChaotic

Complex

EmergenceReflexive AnticipationWill

Science I Science 2

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Ontology

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Science I

Simple

Focus is on Description

Deduction

Complicated

Focus is on ReliablePrediction

Induction via ProbabilisticInference

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Science II

Complex

Focus is on Sagacity(Preparedness)/Resilience/ Robustness

Abduction

Chaotic

Focus is on Pattern Recognition/Identity Assertion

Assert Identity

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The degree of complexity present is the degree to which our chosen

method of reduction has failed

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Challenges to the Representation Model

• Anticipation• Action• Attention• Affordances • Experience• Learning

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Takeaways

Codes are NOT CuesLabels are NOT StoriesHumans are NOT Algorithms

Representations are NOT narrativesContext MattersEfficiency can be the enemy of Resilience

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http://isce.edu

http://isce.edu/mbr.pdf

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