Memes & Changing language - UCSD Cognitive Sciencerik/courses/cogs1_w10/slides/belew-100101.pdf · Memes & Changing language Richard K. Belew Evolution?! • Computational models

© [email protected] Mar 06CogSci 1

Memes & Changing language

Richard K. Belew

Evolution?!

• Computational models of evolution, learning

• Computational analyses of cultural artifacts


What do you think?

•

A B C


“Believing” evolution?

• Gallup, 1997• n=1,000 sampling error +/- 3.2%

• “Intelligent” design?• Randomness?• Science vs. religion?


Preview

• Example of a symbol’s “evolution”

• A computationally precise characterization ofevolution

• Memes

• An experiment!

• Applications in corpus analysis

• General modeling issues for CogSci


Summary

• Evolution is a powerful adaptive process

• Cultures certainly change

• Do “selectionist” models offer the best accounts?

• Vast amounts of new evidence becomingavailable

• The interactions between culture and biologicalevolution will only increase in the future


Summary (cont)

• Key terms

• Replication rate

• Fitness

• Mutation

• Intention

• Temporal/spatial distribution

• Neutral drift


Evolution of symbols

• A Brief History

• Ancient history ...

• ... which ‘evolved’ to exploit a coincidentalmneumonic

• ... which becomes a modern bumper sticker!

• Perhaps an entire species of bumper stickers!

• Survey data T. Lessl]


A Brief History

The fish symbol has been used throughout history by pagan andearth-based religions. Ancient Goddesses in China, Egypt andIndia were represented by the fish symbol. In ancient Greece thefish symbol represented the Goddess of Love. Venus, the ancientRoman empire's Goddess of Love was also represented by a fishsymbol. She was so revered that Christian authorities insisted ontaking over the symbol. The Christians revised the symbol'sassociated mythology to fit their own purposes. Today, the fishsymbol has "evolved" yet again to represent Evolution, Scienceand Political Freedom; as well as all of the topics on our emblemspage.

• According to EvolveFish.com!


Ancient history ...

JesusChristGod’sSonSavior------Fish

• In the beginning there was Christian grafftti


... which ‘evolved’ to exploit acoincidental mneumonic

•


... which becomes a modernbumper sticker!

•


Perhaps an entire species ofbumper stickers!

• http://www.evolvefish.com/fish/emblems.html

DARW IN

Jesus lives!

DARW IN Jesus!


Survey data T. Lessl]

• Survey [Lessl]

• Lessl’s interpreation


Lessl’s interpreation

"By inserting Darwin's name in to the place on the fish iconusually reserved for Christ, the Icthus symbol is rituallyprofaned ," said Lessl, "which is to say, emptied of its religiousmeaning. By putting Darwin's name where Christ's wouldtraditionally go, the Darwin fish does not assert, as one mightthink, that science is salvation and that Darwin is its prophet. Forthe majority of those who display this emblem, Darwin's roleseems to be that of anti-Messiah . This is more like theinversion rituals of carnival, where some drunken peasant isdressed up as the king. Its purpose is not to elevate the peasantbut to make fun of the king."

•


Evolution

• Charles Darwin (1809 -1882)

• Definitions

• Basic algorithm

• GA at a glance

• Structured populations


Charles Darwin (1809 -1882)

• Replication

• Mutation

• Selection


Definitions

• Individual xi = (0,1)L ; string of L bits

• Population X = xi ; |X| = P, size of

population

• Generation Xt ; population at a pointin time


Basic algorithm

Create X0, randomlydo ; “Generation”

forall xi in X

Evaluate fitness f(xi) in R

Determine num. offspring g(xi) in J ; ∑ g(xi) = P

Form Xt+1 = g(xi) copies of xi

Apply genetic operators Ω to Xt+1

until Xt+1 has converged ; (X ≈ Xt+1)


GA at a glance

101010111010100010010111010100101001001011011011010101010101001001001011011110110101010101101011010101101010010101010110

0.2560.6730.3540.5430.4290.8670.2170.3160.6320.5640.5360.5650.4560.9310.101

<f(x)>=0.496

011112012111030

101010001001011101010010100100101101101111011011010100100100101101001011011110110101010101101011101001011010010110100101

101010001001011101010010100100101101001111011011010100100110101101001011011110110101010101100111101010011010010110100101

Mutation

Crossover

Xt Xt+1f(x) g(x)


Structured populations

• Island models

• Minimal gene flow

• 2d version


Memes: Cultural analog of gene

• “Replicator in the soup of human culture, ... unitof cultural transmission, of imitation”

• Dawkins’76, Chap11 (revised 1989)

• D. Campbell (1974): Evolutionary Epistemology

• Other biologically inspired models of culture

• Cavalli-Sforza & Feldman (1981)

• Boyd & Richerson (1985)


Experimental Memetics

• Experiment(22 jan 03)

• Algorithm


Algorithm

1. Divide your piece in half

2. Optional: Add ‘graffiti’• If you do, add the SAME graffiti to all instances on half• You can add different notes to the two halves

3. Pass your two halves to two neighbors• Odd: Front/Back• Even: Left/Right

4. SELECT: your favorite ONE from the TWOsheets passed you

• (Wad up the other; we’ll collect)

Go to #1


Dan Dennett

• What kind of biological analogy?

• Virus?

• Symbiotic host/guest

• Parasite: negative effect on host

• Commensal: neutral

• Mutual: positive

• “Genes hold culture on a leash” [E. O. Wilson]


Dan Dennett (cont)

• Intentional stance (on cultural analysis)

• “analyzing the flux of events in terms of agentsand their (rational) actions and reactions”

• “a meme is an information packet with anattitude”

• Intention + biology = genetic engineering! [P.Kitcher, Lives to Come]


Dawkins’ data!

• “If the meme is ascientific idea... a roughmeasure of its survivalvalue could be obtainedby [its citation count]” -1976

• 1989 notes, citations to[Hamilton’64] used asevidence ofEXPONENTIAL growth

• In distinction to simplyCUMULATIVE citationrates, ala influentialother influential texts


Evolution, Development,Learning, Culture

• Adaptation as sine qua non of cognitive system

• Adaptation to invariants of environmentat varying time-scales

• Cultural change

• Evolution as primary adaptive system

• Interaction among adaptive mechanisms


Adaptation as sine qua non of cognitive system

What is invariant in adaptive systems will depend on the timeintervals during which we observe them. There are at leastthree time scales of relevance to such systems,corresponding to three different forms of adaptation. - On the shortest time scale intelligent --- hence adaptive ---systems continually change their behavior in the course ofsolving each problem situation they encounter.... - On a somewhat longer time scale, intelligent systemsmake adaptations that are preserved and remain available formeeting new situations successfully.... - On the longest time scale, intelligent systems evolve.

“Cognitive Science: The newest science of the artificial”H. Simon, 1980


Adaptation to invariants of environmentat varying time-scales

Environmentalvariation


Cultural change

• Slower than individuals can change• But faster than evolution can adapt

Environmentalvariation


Evolution as primary adaptivesystem

• Chronologically

• (The?) defining characteristic of living systems

• Emergence of subsequent adaptive mechanisms

• Ontogenesis

• Learning

• Culture


Interaction among adaptivemechanisms

• Only models subsuming multiple adaptivemechanisms can speak to interactions amongthem

• But the constituent models (eg, of evolution,learning, etc.) will necessarily be simplified

• Confusions abound• “Inheritance of acquired characteristics” [Lamarck]• “Ontogeny recapitulates phylogeny” [Haeckel]• “Nature” XOR “nurture”?• “Nativist” XOR “empiricist”?• “Race predicts IQ”

Adaptive Indivuals in Evolving Populations Richard K Belew © 2004NBU Summer School - 19 Jul 04

Inheritance of acquiredcharacteristics [Lamarck]

•

Ph(t2)Ph(t1)

G(t3)G(t0)

Time

Evolution

Development

Learning

Lamarck was wrong!No reverse transcription

Adaptive Indivuals in Evolving Populations Richard K Belew © 2004NBU Summer School - 19 Jul 04

Mediating environment

•

Ph(t2)Ph(t1)

G(t3)G(t0)

Time

Evolution

Development

Learning

Lamarck was wrong!No reverse transcription

Gamete

Development

Soma

Environment

Learning

BaldwinEffect

CriticalPeriods

Behavior

Baldwin effect

Even if we accept [that individuals' learning cannot alter informationin the gene], it is still possible for individual learning to facilitateevolution. If individuals vary genetically in their capacity to learn, orto adapt developmentally, then those most able to adapt will leavemost descendants, and the genes responsible will increase infitness. In a fixed environment, when the best thing to learnremains constant, this can lead to the genetic determination of acharacter that, in earlier generations, had to be acquired afresheach generation. [John Maynard Smith]

•


Summary

• Evolution is a powerful adaptive process

• Cultures certainly change

• Do “selectionist” models offer the best accounts?

• Vast amounts of new evidence becomingavailable

• The interactions between culture and biologicalevolution will only increase in the future


Summary (cont)

• Key terms

• Replication rate

• Fitness

• Mutation

• Intention

• Temporal/spatial distribution

• Neutral drift

Documents

Memes & Changing language - UCSD Cognitive Sciencerik/courses/cogs1_w10/slides/belew-100101.pdf · Memes & Changing language Richard K. Belew Evolution?! • Computational models