1 © Amit Mitra & Amar Gupta TOPICS READING ASSIGNMENT: SUPPLEMENTARY MATERIALS MODULE 5 Domains of meaning vs. Format Representation and its polymorphisms

1

© Amit Mitra & Amar Gupta

TOPICSREADING ASSIGNMENT: SUPPLEMENTARY MATERIALS MODULE 5

• Domains of meaning vs. Format

• Representation and its polymorphisms

• The architecture of Pattern

– Properties of patterns

– Meaningful patterns of information

• Meanings in information space

• FORMATS AND MEASURES

– Precision, size, dimensionality and capacity for conveying information

– Number vs. Value

– Information payload and “Full Format” of a meaning

– Domains of meaning

– Assembling meanings

– Domains of information quality

SEE SUPPLEMENTARY

MODULE 4

YOU WILL NEED SOUND FOR THIS PRESENTATION

2


Domains• Domains of information

– Domains of meaning– Domains of numbers– Formatting domains

• Domains of meaning are the wellspring of meaning– The most elementary patterns in information space from which meanings are assembled– Emerge from the concept of measurability

• But is different from the concept of “Number”– The length of this room will not change whether we call it 12 feet ot 144 inches– Numbers may represent values in a domain under certain conditions

• Maps between sets, like the figures in Box 33 of supplementary materials

• A map that preserves the order of values (if known)

• Meanings must be represented by formats to physically communicate the abstract information they hold– Speech, text, graphics etc.

• Symbol=Format (co-domain of the meaning, may be many)

• Mapping rule=Formatting Rule

The least abstract of the three kinds of domains; we will discuss this domain first

objectValue A1 value C1(image of value A1)

RULE

DOMAINOF RULE

CODOMAINOF RULE

3


Object SymbolSubtype of

Subtype of

Subtype of

Format Translation is also a polymorphism of the generic representation relationship

between objects

Format is a polymorphism of the generic representation

relationship between objects

Generic representation relationship between objects

An object may be thought of as representing itself, but that conveys no information

A symbol may or may not represent an object

• Homonyms and synonyms are polymorphisms of Representation

• Similies and encryption are forms of representation– Encrypted meanings or formats?

• Agents are representatives

The Eagle has

landed

See supplementary materials box 36

4


PERCEPTION AND COMMUNICATION OF MEANING• Five fundamental formatting domains based on five

senses

–Visible (Visual) Formats: normalizes behavior common to visual perception

– Eg: 3d, movement and rotation in space, viewpoints from different locations, color, size, contrast, brightness, etc.

• Script: Written symbols such as alphabets, numerals and words

• Graphics: diagrams, pictures etc.

–Audible (Audio) Formats: normalizes behavior common to audible perception

– Eg: loudness (volume), pitch

–Tactile (Haptics) formats: normalize behavior about touch

– Eg: feeling of pressure, roughness or smoothness, heat or cold, hardness and softness, sharpness or bluntness, friction etc.

–Olfactory Formats: normalizes behaviors natural to sense of smell

–Taste Formats: normalizes behaviors natural to sense of taste

• Bridge between Business and Interface Layers

TECHNOLOGY RULES

INTERFACE RULES(HUMAN & AUTOMATION)

INFORMATIONLOGISTICS

BUSINESSRULES

Vision

Proce

ssEve

nts

Value

Policy

/Stra

tegy

Excep

tions

BUSINESSPATTERNS

DATA MOVEM

ENT

GUIs & F

ORMATTIN

G

COMPONENTS

PERFO

RMAN

CE OPTI

MIZ

ATION

COM

PONEN

TS

2

Meaning to algorithm or formula

1

6

PARTITION

Object SymbolSubtype of

Subtype of

Subtype of

Meaning

What is a Pattern?

• A pattern is an arrangement

–Follows a law

•The law/algorithm increases predictability, reduces/(does not increase) information content–Eg: Spelling, 1+2=3; 1,2,1,2,1,2..;

Law of Location

Could be combinations of symbols across formatting do,mains eg: multimedia

Determines the identity & meaning

of the pattern

Projects abstract meanings into physical

space and time

Constrained in physical space

and time

Sounds in a region of

physical space for a span of

time

7


Symbol

May be pattern of 0 or more[be part of 0 or more]

FORMATTINGDOMAIN

(Domain of Symbols)

Mem

ber of

8


PATTERNS/SYMBOLS IN THREE SPACE

HEIGHT

WIDTH

LENGTHOrigin

Different symbols (patterns)

Pattern

PatternsSeparation

Separation

Separa

tion

(Same Size, Rotated)

(Different and same sizes, Rotated)

Angular separation of symbols in a pattern

Same or different pattern?

Same or different pattern?

?

?

?

(Mirror Images)Same or different pattern? ?

(Same Size & orientation,Different positions)

– why do we think they are

different?

Same or different pattern? ?

9


FUNDAMENTAL STATES OF THE LAW OF LOCATION (2)• Shape might matter, but not size

– Angles are preserved, but not linear distances• Preserves some, but not all information on size

HEIGHT

WIDTH

LENGTHAngle 1

Angle 2Distance from origin

Origin

Location

• The shape might matter, not orientation– Relative, not absolute separation is important

Considered identical patterns

Considered identical patterns

Considered different patterns

10


DIMENSIONALITY OF A PATTERN - DEGREES OF FREEDOM

HEIGHT

WIDTH

LENGTHOrigin

11


FUNDAMENTAL PROPERTIES - DEGREES OF FREEDOM

Distance from origin

HEIGHT

WIDTH

LENGTHAngle 1

Angle 2Origin

3 degrees of freedom

12

32

1

2

12


FUNDAMENTAL PROPERTIES OF PATTERNS- DEGREES OF FREEDOM

HEIGHT

WIDTH

LENGTHOrigin

Degrees of freedom of the ensemble? 3 x 3 = 9Ensemble

2 x 2 = 4

Degrees of freedom of a line in 2-space? 2 x 2 – 2 – 1 = 1

•Degrees of freedom depends on the law of location–Dimensionality of conceivable state space

•Eg: Written words are 1 dimensional, maps are 2 dimensional–Constraints

•Dimensionality and shape of pattern/lawful state space

Degrees of freedom of a line in 3-space: 3 x 3 – 3 – 1 = 5

Which Pattern has more freedom:

“Ancestor” or “Grandfather”

?

Money

Num

ber

of p

iece

s

Money per piece

Hole

The information could also be formatted in strings of numbers, patterns of colors, etc.

Formats are like pipes that convey abstract

information from information space to

physical space. Like a pipe, a symbol has limited capacity to convey

information. The information carrying

capacity of a symbol is determined by its degrees

of freedom

Object

Information Payload

See supplementary

Box 37, 38

13


FUNDAMENTAL STATES OF THE LAW OF LOCATION• FUNDAMENTAL PROPERTY: Association – Which objects are associated with which

– Eg: In physical space a point is connected to points in its neighborhood and the separation between points in a neighborhood is infinitesimally small

– All spaces may not have a neighborhood• Eg: nominally scaled space

• FUNDAMENTAL PROPERTY: Sequence – Sequence matters (or not)

– Sequenced vs. unsequenced association

UnsequencedAssociation

SequencedAssociation

Eg: Spellings, words, sentences

– Incomplete Order• In multidimensional space (eg: physical space), order may count only in some directions

– Eg: when the pattern does not distinguish between mirror images

Eg: Concept “Joined in matrimony”

Rules of (unsequenced)

association

Sequencing Rules

Subtype

• Information content and density of the pattern may be different in different directions in information space

14


FUNDAMENTAL STATES OF THE LAW OF LOCATION• FUNDAMENTAL PROPERTY: Separation – Whether distance matters (or not)

– Independent of sequence

– Distance = Measure of Similarity• Proximity Metric

– (see notes on generalizing distance in your text book)

– Patterns of separation• Collocation/distinction, ordinal separation, quantitative separation

• Collocation has no information on order– Eg: if the tone and the icon were constrained to occur together, we could not say which occurred before which

• FUNDAMENTAL PROPERTY: Pattern of inclusion vs. Exclusion

– Eg: Movie with sound vs. Mime/silent movie• FUNDAMENTAL PROPERTY: Extent (of pattern) – how far does the overall pattern extend in information space?

– Infinite vs. finite patterns• Eg: Ancestor vs. Parent

• FUNDAMENTAL PROPERTY: Delimitation (of pattern) – does the pattern have boundaries in information space?

– Delimited vs. undelimited patterns

– Infinite patterns will have no boundaries

The proximity metric between a pair of points in state space

cannot exceed the sum of the same measure via intermediate points in between the points in

the pair

Finite patterns may or may not have boundaries!!

15


Fundamental states of the law of location are the universal properties of patterns

DISKDISKCIRCLE(a different pattern)

DelimiterDelimiter

Delimiter (of letter)

Beginning

(of word)(space)

FUNDAMENTAL STATES OF THE LAW OF LOCATION

Finite, bounded delimited pattern Finite, unbounded

patternFinite pattern unbounded in one direction, delimited in another

End Delimiter Pattern of Infinite

Extent

FiniteUnbounded

Pattern

DelimitedPattern

Subtype of

Subtype of

Eg: Time

Eg: Year

Eg: Calendar Year

BoundedPattern

EXAMPLESOpen

BoundedPattern

ClosedBoundedPattern

Partition

Delimiter

• Boundaries (or not)

– Delimiters (or not)• Patterns (symbols) may delimit patterns

(symbols)

• Order, Punctuation

16


TIME

(EXAMPLE) A MATTER OF TIME

Delimiter: Jan1

17


Pattern of Infinite Extent

FiniteUndelimited

Pattern

DelimitedPattern

Subtype of

Subtype of

Delimiters are meaningless, but ad-hoc sets of states may define regions of state space

Open and closed delimiters may express the same meaning

DelimitedPattern

WHAT KINDS OF PATTERNS MAY EXIST IN WHICH KINDS OF SPACE?

OpenBoundedPattern

ClosedBoundedPattern

NOMINAL SPACE

ORDINAL SPACE

DIFFERENCE SCALED

SPACE

IMPLIED: ALL THESE KINDS OF PATTERNS MAY ALSO EXIST IN RATIO SCALED SPACE

Bounds and Delimiters are meaningless

18


THE PROXIMITY METRIC

Value ConstraintProximity of a pair of

states cannot exceed the summation of

proximities of states over any trajectory that connects the pair

constrain[constrained by]

Measure of similarity between 2[similarity may be measured by 0 or more]

Nominal Proximity

Metric

Nominal Proximity

Metric

Ordinal Proximity

Metric

Ordinal Proximity

Metric

Ratio Scaled

Proximity Metric

Ratio Scaled

Proximity Metric

Difference Scaled

Proximity Metric

Difference Scaled

Proximity Metric

Subtype of

STATE




Subtype of

Subtype of

Proximity Metric

Subtype of

NOMINALSTATE

ORDINALSTATE

QUANTITATIVELY SCALED STATE•Difference scaled state•Ratio scaled state

Value ConstraintThe proximity between a pair of

dissimilar states cannot be Nil or less

Value ConstraintThe proximity of a state to

itself must be nil

Value ConstraintThe proximity between a pair of states

must be the same in both directions

When we know items exist, but have no idea of their similarity, or even co-location (identity)

A Proximity Metric lies at the heart of every pattern•An attribute of Pattern•A kind of distance

Rules

MEASURE OF PROXIMITY KIND OF SPACE Nominal Ordinal

Difference Scaled Ratio Scaled

Nominally Scaled

(only two values – nil and more than

nil)

Ordinally Scaled


MEASURE OF PROXIMITY KIND OF MIXED SPACE Nominal Ordinal


One or more Nominally Scaled axes

(only two values – nil and more than

nil)

No Nominally Scaled axes One or more Ordinally Scaled axes

No Nominally or Ordinally Scaled axes One or more Difference Scaled axes

Only Ratio Scaled axes (not a mixed Space)

19


Parameter/ Feature

Directional? Subtypes Valid in (Space)

Association Y Patterns of Associations All

Sequencing Patterns Ordinal

Dimensionality N Dimensionality of state space All

Dimensionality of pattern Ordinal & subtypes

Cohesion/ Separation

Y Patterns of distinction All

Ranking patterns Nominal & Subtypes

Patterns of separation in terms of quantitative differences (eg: differences in military rank)

Ordinal & Subtypes

Patterns of separation in terms of ratios of separation (eg: Physical distance)

Difference scaled & Subtypes

Location Y Absolute location Spaces with “Nil” value (Ratio scaled and Ordinal with Nil value)

Differences in absolute location Ordinal with Nil value

Ratios of absolute location Ratio scaled space

Inclusion vs. Exclusion

Y Patterns of inclusion Nominal & Subtypes

Patterns of exclusion Nominal & Subtypes

Extent Y Infinite Nominal & Subtypes

Finite Nominal & Subtypes

Delimitation Y Unbounded (Undelimited) Nominal & Subtypes

Bounded (Delimited) Ordinal & Subtypes

Open Difference Scaled & Subtypes

Closed Difference Scaled & Subtypes

UNIVERSAL PROPERTIES OF PATTERNSO

rder of a p

attern(p

attern of p

atterns, p

attern of p

attern of p

atterns etc.)

Deg

rees

of

free

dom

(in

form

atio

n c

arry

ing

cap

acit

y)Partition

Subtype ofCardinality

(No. of participating Objects)

May be infinite

• Dime nsio nalit y o f sta te spa ce

• D imensionality o f patt ern• D irect io n(s) i n patt ern• Ag gre ga te St at ist ics a bo utlo ca tion and sepa rat ion o fc omponents (e .g . va rian ceof separatio ns)

PATTERN

Regionof StateSpace

(Range)

PAT TE RN DEL IMIT ER(B OUND )

B e gin Delimit er

E nd Delimit er

B eg in/En d P ar titio n

Cl osedDelimit er

O penDelimit er

Su

bty

pe o

f

Cl osed/O penD elimiter P ar tition

O BJECT I NSTA NCE

Co nstra ins 0 o r mo re[const rained by 0 o r m or e]

O bje ctO ccurrence

V alue

Exc lude reg ion o f

CONSTRAIN

Inc usio n /Exc lusionPartit ion

(C )

L aw o fInteract ion

Set o fO bject St ates(Stat e S pace )

O bjec tStat e

Se ts a re equa l

Subtype o f

Co nta ins 0 o r mo re[co nta ined in 0 o r m or e]

( imp lied)

Sequenced

Regionof StateSpace

M a y be delim it ed by 0 o r mo re[de lim i t 1 o r m ore ]

(inhe rited)

Subty peo fSubty pe

o f

Q ua nti tatively

Scaled Regionof State Space

M a y be delim it ed by 0 o r mo reu nsubst itutable

[de lim i t 1 o r m ore ](inhe rited)

M a y be delim it ed by 0 o r mo reu nsubst itutable

[de lim i t 1 o r m ore ](inhe rited)

not delimite d by

delim it ed by 1 o r more

Delimita tio nP a rtit io n

(E )

C2

C1

E1

E2

Inc lude reg ion o f

M a y be delim it ed by 0 o r mo re

Subtype o f

unsequenc ed pa tt ern delimit er

Sequenc edPatte rn

Delimit er

Seq ue nced/Unseque ncedD elimiter P ar titionBe gin Pa tt ern Delimit er

E nd Patt ern Delimit erInfinit e Patte rn

Fi nit e Patt ern

EXTE NTP a rtit io n

(D )

D1

D2

Se nse d in 1 o r more[co nta in 1 o r m ore ]

Sym bo l

pat ter n o f 0 o r mo re[be co nta ined in 0 o r m ore ]

Subtype o f

E numerates O ccurre nce of 1[Occu rrence e nume rated by 1 ]

FOR M AT TING

DO MAI N

Vis ua lDoma in

Audib leDoma in

OlfactoryDoma in

Ta cti leDoma in

Ta steDoma in

FU NDAME N TAL FOR M AT TING DO MAI NS

E nume rated in 1[ has 1 o r m ore ]

pa rtit ion o f[ par titio ned by ]

K IND O FDEL IM IT ER

K IND O FDEL IM IT ER

Open De li mit ed Patt ern

KIND

OF

PAT

TERN

Se que nced Delimit ed Patte rnK IND O F

P AT TER N

M a y be delim it ed by 0 o r mo re[de lim i t 1 o r m ore ]

(inhe rited)

Subty peo f

STATE SP ACEOF P AT TER N

Subty pe( role) o f

•Dimensiona lity•Dir ectio n

L aws of absolut e loca tio n

B4

L aws o fSepar at io n

(B )L oca tio nP a rtit io n

(F )

F1

B3

F2

B1

B2


Su bty pe ( role) o f

o f 0 or m

ore

[in 1 ]

Set o f 0 or more[ in 1 o r m ore ] C annot

ex ceedDimensiona lity(of stat e space )

Dimensiona lity(o f pat ter n)

Subtype o f

•O rder•Degrees o f Freedo m


Loca te sequenc ed

Seq ue nced/Unseque ncedA sso cia tio n P a rtitio n

(A )

A1

A2

Pa tt ern o fco lloca tio n

K IND O FP AT TER N

L o cate unse que nced

Subtype o f

Locate d in 0 or more

[pa tt ern of 1 or more ]

2 ..*

he ld in 1 0 r mo re[holds 0 or m ore ]

*

Aggre ga te o f 2 o r mo reAg g reg ated by 0 o r mo re

( inherit ed)•Dimensiona lity

•Dir ectio n


•Dir ectio n


•Dir ectio n

Subtype o f

A rra ysP at tern in Discre te Spa ce

Pa tte rn in phys ical spa cea nd time

Subtype o f

KIND OF

P ATTER N

Subtype o f

Sequenced Pattern(ordered list)

Pattern in PhysicalSpace and Time

Pattern ofcollocation

Su

btyp

e of

Unsequenced Pattern(unordered list)

Patterns with noseparation in state space

(Subtypes In Partition)

Partition of[Partitioned into]

(A2)

Pattern of inclusion

Pattern ofexclusion

INCLUSION/EXCLUSIONPARTITION

(C)


(C2)

(C1)

Symbol

Other Fundamental Attributes•Dimensionality of pattern•Dimensionality of State Space•Degrees of freedom•Order of the pattern.

Time: 1 dimensional patternsPhysical Space: 1, 2 and 3 dimensional patterns

Physical Space-Time: 2, 3 and 4 dimensional patterns


Sub

type

of

Sequenced Delimited Pattern

Sub

typ

e of

May delimit 0 or more[be delimited by 0 or more]

May be pattern of 0 or more[be contained in 0 or more]

Open Delimited Pattern

Pattern Delimiter

Sequenced Pattern Delimiter

BEGIN/END PARTITION

Unsequenced Pattern DelimiterSEQUENCED/UNSEQUENCED DELIMITER PARTITION


Begin Pattern Delimiter


Delimited Pattern

Undelimited Pattern (E1)

Subtype of

Delimit 1 or more[delimited by 1 or more]

End Pattern Delimiter


(inherited)

Subtypeof


Infinite Pattern

Finite Pattern

EXTENTPARTITION

(D)


(D2)

(D1)

LOCATIONPARTITION

(F)


Pattern ofSeparation between

States

Pattern of absoluteStates

(F2)

(F1)

Label for directionalpartition in State Space

Pattern ofDistinctions between

States

SEPARATIONPARTITION

(B)


(B1)

Pattern ofDifference Scaled

Separation

Pattern of OrdinalSeparation

(B3)

(B2)

(E2)

Su

btyp

e of

(A1)

SEQUENCED/UNSEQUENCEDASSOCIATION PARTITION

(A)

Su

btyp

e of

DELIMITATION PARTITION(E)


Patterns of RatioScaled Separation(B4)

(For example, distances in physical space)

Su

btype of

Sub

typ

e of

Object

22©20066 Amit Mitra & Amar Gupta

(For example, distances in physical space)

constrain[constrained by]

Measure of similarity between 2[similarity may be measured by 0 or more

NominalProximity

Metric

OrdinalProximity

Metric

RatioScaled

ProximityMetric

DifferenceScaled

ProximityMetric

Value ConstraintProximity of a pair of

states cannot exceed thesummation of

proximities of states overany trajectory thatconnects the pair

Subtype of

STATE




Subtype of

Subtype of

ProximityMetric

Subtype of

NOMINALSTATE

ORDINALSTATE

QUANTITATIVELY SCALED STATE•Difference scaled state•Ratio scaled state

(B1)

(B3)

(B2)

(B4)

PATTERN

Regionof StateSpace

(Range)

PATTERN DELIMITER(BOUND)

Begin Delimiter

End Delimiter

Begin/End Partition

ClosedDelimiter

OpenDelimiter

Closed/OpenDelimiter Partition

Subtypeof

OBJECTINSTANCE

Constrains 0 or more[constrained by 0 or more]

ObjectOccurrence

ValueSet of

Object States(State Space)

Sets are equal

Subtype of

SequencedRegionof StateSpace

Subtype (role) of

May be delimited by 0 or more[delimit 1 or more]

(inherited)

SubtypeofSubtype

of

QuantitativelyScaled Regionof State Space

May be delimited by 0 ormore unsubstitutable[delimit 1 or more]

(inherited)

May be delimited by 0 ormore unsubstitutable[delimit 1 or more]

(inherited)

May be delimited by 0 or more

Su

bty

pe

of

Sensed in 1 or more[contain 1 or more]

Symbol

pattern of 0 or more[be contained in 0 or more]

Su

bty

pe

of

Enumerates Occurrence of 1[Occurrence enumerated by 1]

FORMATTINGDOMAIN

VisualDomain

AudibleDomain

OlfactoryDomain

TactileDomain

TasteDomain

FUNDAMENTAL FORMATTING DOMAINS

Enumerated in 1[has 1 or more]

May be delimited by 0 or more[delimit 1 or more]

(inherited)

Su

bty

pe

of

Su

bty

pe

of

Subtypeof

STATE SPACEOF PATTERN

Subtypeof

held in 1 or more

[holds 0 or more]

Dimensionality(of state space)

Dimensionality(of pattern)

Cannot exceed

Located in 0 or more[pattern of 1 or more]

2..*

*

Agg

rega

te o

f 2

or m

ore

Agg

rega

ted

by

0 or

mor

e

Subtypeof

Subtypeof

Subtype of

Directional Patternin State Space

ArraysPattern in Discrete Space

Pattern in physical space and time

Subtypeof

Subtypeof

Represent 0 or more other[represented by 0 or more other]

*

Represent 0 or more other[represented by 0 or more

Subtype ofSu

bty

pe

of

Represent 1 or more[represented by 1 or more]

Sequenced Pattern(ordered list)

Pattern in PhysicalSpace and Time

Pattern ofcollocation

Subt

ype

of

Unsequenced Pattern(unordered list)

Patterns with noseparation in state space



(A2)

Pattern of inclusion

Pattern ofexclusion

INCLUSION / EXCLUSIONPARTITION

(C)


(C2)

(C1)

Object

Other Fundamental Attributes•Dimensionality of pattern•Dimensionality of State Space•Degrees of freedom•Order of the pattern.

Time: 1 dimensional patternsPhysical Space: 1, 2 and 3 dimensional patterns

Physical Space-Time: 2, 3 and 4 dimensional patterns


Subt

ype

of

Sequenced Delimited Pattern

Subt

ype

of

May delimit 0 or more[be delimited by 0 or more]

Open Delimited Pattern

Pattern Delimiter

Sequenced Pattern Delimiter

BEGIN/END PARTITION

Unsequenced Pattern DelimiterSEQUENCED/UNSEQUENCED DELIMITER PARTITION


Begin Pattern Delimiter


Delimited Pattern

Undelimited Pattern (E1)

Subtype of


End Pattern Delimiter


(inherited)

Subtypeof


Infinite Pattern

Finite Pattern

EXTENTPARTITION

(D)


(D2)

(D1)

LOCATIONPARTITION

(F)


Pattern ofSeparation between

States

Pattern of absoluteStates

(F2)

(F1)

Label for directionalpartition in State Space

Pattern ofDistinctions between

States

SEPARATIONPARTITION

(B)


(B1)

Pattern ofDifference Scaled

Separation

Pattern of OrdinalSeparation

(B3)

(B2)

(E2)

Subt

ype

of

(A1)

SEQUENCED/UNSEQUENCEDASSOCIATION PARTITION

(A)

Subt

ype

of

DELIMITATION PARTITION(E)


Patterns of RatioScaled Separation(B4)

Subtype of

Subt

ype

of

Directional Patternin State Space


Partition of[Partitioned into]Partition of

[Partitioned into]

Subtype of

May be pattern of 1 or more[be contained in 0 or more]

23©20066 Amit Mitra & Amar Gupta

The Metamodel of Pattern• The Metamodel of Pattern is the Metamodel of Object

– And the Metamodel of Constraint• Constraints carve objects out of information space• Add information to an object or pattern

• External objects may shape a pattern– By influencing its parameters

• Location, proximity metric, inclusion/exclusion, degrees of freedom etc.

– Influencing the shape of the pattern and participating in a pattern are different and independent roles of Object• The concept of Context emerges from this

• Pattern is held in State Space– Held In is the aggregation of “Locate”, root of enumeration and other emergent properties of object classes/aggregates

• Arrays and tables are a kind of discrete pattern in multidimensional state space• Physical space/space-time is a constrained form (polymorphism) of information space

– Patterns in and space and time are symbols constituted of physical objects/energy, constrained to only one region of physical space at a given point in time

• Polymorphisms of patterns in information space

• Null space is the region of null values, i.e., forbidden regions in information space– Meaninglessness is a polymorphism of null space, a stricter form of impossibility

Object

Information PayloadInformation Payload

ObjectInstance 1

ObjectInstance 2

ObjectInstance 3

Attribute1

Attribute2

Attribute3 Tim

e Slices

Present

Past

History of Attribute 3across all object instances

Current values of attributes for each

object instance

State history ofObject Instance 3

B

A

C

12

3

Documents

1 © Amit Mitra & Amar Gupta TOPICS READING ASSIGNMENT: SUPPLEMENTARY MATERIALS MODULE 5 Domains of meaning vs. Format Representation and its polymorphisms