Language as a culturally evolving system: from computer simulation - - PowerPoint PPT Presentation

Language as a culturally evolving system:

from computer simulation to the experiment lab

Simon Kirby

Language Evolution and Computation Research Unit School of Philosophy, Psychology & Language Sciences University of Edinburgh

T H E U N I V E R S I T Y O F E D I N B U R G H

Why don’t we have the answers yet?

• Language is our species defining characteristic
• Surely we should know where it came from by now?

Why don’t we have the answers yet?

• Language is our species defining characteristic
• Surely we should know where it came from by now?
• Language evolution is: “the hardest problem in

science” (Christiansen & Kirby 2003)

• Why?

There’s something special about language

• It arises from 3 interacting dynamical

systems

• Biological evolution of a capacity for

learning languages that are transmitted culturally over space and time in a speech community

• Arguably, no other single behaviour in

nature has such complex a source

• So, how do we go about tackling this?

CULTURAL TRANSMISSION INDIVIDUAL LEARNING

LANGUAGE

BIOLOGICAL EVOLUTION

Idealisations

• A foundational idealisation:

the idealised speaker/hearer in a homogenous speech community

• Abstract away from complex social/cultural/

population aspects

• The nativist approach:
• focus on individual’s faculty of language

acquisition Universal properties

• f individual cognition

Universal properties

• f language

Idealisations

• A foundational idealisation:

the idealised speaker/hearer in a homogenous speech community

• Abstract away from complex social/cultural/

population aspects

• The evolutionary/nativist approach:
• focus on individual’s faculty of language

acquisition

• treat as a biological adaptation for

communication

• universals of language arise from universal

biological adaptation Universal properties

• f individual cognition

Universal properties

• f language

Genes “for” language

?!

The missing process

• The individual-centric idealisation leaves out cultural transmission, precisely

because we don’t understand it well

• Leading questions:
• Are there other idealisations we could make that would allow us to look at

the full complexity of the adaptive systems at play?

• Can we be sure that the basic assumptions we’ve outlined are correct?

Do properties of the individual get straightforwardly “written out” in the structure of language? Are there alternative mechanisms explaining adaptive structure of language?

The iterated learning model

• Cultural evolution of language is of a

particular type:

• Simulate this process in the computer
• Embed simple models of learners in an

“environment” that they want to communicate about

• Agents learn from others’ behaviour (cf.

the game “telephone”)

ITERATED LEARNING: Learning by observation of behaviour in another that was itself learned in the same way.

INTERNAL REPRESENTATION OBSERVABLE BEHAVIOUR INTERNAL REPRESENTATION OBSERVABLE BEHAVIOUR

PRODUCTION LEARNING LEARNING PRODUCTION LEARNING

Quick summary of the results from simulations

• Key insight: transmission bottlenecks
• If a learner is given imperfect information about the language, e.g. noise,

processing constraints, or simply not hearing all the data (cf. stimulus poverty)

• ... cultural transmission becomes an adaptive system.
• Language will adapt so that it appears to be designed to “fit” the

bottleneck

• Has been used to explain some of the design features of language,

particularly compositionality

Design without a designer

• Languages (arguably) have the appearance of design
• Two obvious mechanisms to explain this:
• Biological evolution (leading to the evolutionary/nativist view)
• Intentional design by individuals
• Computational models suggest an alternative
• Cultural evolution
• Consistent with the idea of the “invisible hand” (Keller 1990)
• But can we demonstrate this with real human agents?

Cumulative cultural evolution in the laboratory: An experimental approach to the origins

• f structure in human language

Simon Kirby*†, Hannah Cornish*, and Kenny Smith‡

*School of Philosophy, Psychology, and Language Sciences, University of Edinburgh, Edinburgh EH8 9LL, United Kingdom; and ‡Division of Psychology, Northumbria University, Newcastle-upon-Tyne NE1 8ST, United Kingdom Edited by Dale Purves, Duke University Medical Center, Durham, NC, and approved June 6, 2008 (received for review August 20, 2007)

An experimental approach

• Inspired by work of Galantucci, Garrod, Fay and others, we tried to replicate

simulations in the experiment lab (Kirby, Cornish & Smith, 2008)

• Cultural transmission of an “alien” language
• 1. Start with a random artificial language
• 2. Ask experimental participant to learn language and test them
• 3. Use their output at test to teach the next participant in the experiment

(and repeat)

Hypothesis

• There will be cumulative cultural adaptation of the language without

intentional design by the participants

• Two ways of verifying this:
• The language should become easier to learn
• The language should become structured

The language

• Simple syllable sequences for coloured moving shapes.
• For example:
• 27 “meanings” in total (3 shapes, 3 colours, 3 motions)

kapihu luki nelu kalu moki kilamo

Procedure

• Language divided randomly into two sets:
• SEEN set: 14 meaning-signal pairs
• UNSEEN set: remaining 13 meaning-signal pairs
• Subjects trained only on SEEN set
• Tested on complete set
• Output on test randomly redivided into new SEEN and UNSEEN sets for next

generation

Results

• 2

4 6 8 10 5 10 Generations Structure

• 2

4 6 8 10 0.0 0.2 0.4 0.6 0.8 1.0 Generations Error

a) b)

Language becomes easier to learn, and structured

After generation 1

kimei miwn miheniw pemini kupini pon poi mhip kuwpi mip mpo miniku nige poh tuge weg kuhepi wige mie hepinimi himini hipe pobo tupim

After generation 6

miniku tupim tupin tuge poi minku

After generation 7

miniku tupim tupin tuge poi

miniku tupim tupin tuge poi

After generation 8

miniku tupim tupin tuge poi

After generation 9

miniku tupim tupin tuge poi

After generation 10

Language adapts

• Language adapts to be structured and learnable
• Polysemy emerges that underspecifies the meaning-space in clever ways
• Subjects are unaware of this happening

Language adapts

• Language adapts to be structured and learnable
• Polysemy emerges that underspecifies the meaning-space in clever ways
• Subjects are unaware of this happening
• But it’s not a particularly exciting form of structure!
• Need a way of forcing the language to be expressive
• Second experiment: simply discard words at random from SEEN set

before training if they do not discriminate meanings

• 2

4 6 8 10 5 10 Generations Structure

• 2

4 6 8 10 0.0 0.2 0.4 0.6 0.8 1.0 Generations Error

a) b)

Results

Language becomes structured and easier to learn

Generation 1

lumonamo kinahune lahupine nelu kanehu namopihu kapihu humo lahupiki moki luneki lanepi kalu mola pihukimo nane kalakihu mokihuna kilamo kahuki neluka pilu neki pinemohu luki namola lumoka

n-ere-ki l-ere-ki renana n-ehe-ki l-aho-ki r-ene-ki n-eke-ki l-ake-ki r-ahe-ki n-ere-plo l-ane-plo r-e-plo n-eho-plo l-aho-plo r-eho-plo n-eki-plo l-aki-plo r-aho-plo n-e-pilu l-ane-pilu r-e-pilu n-eho-pilu l-aho-pilu r-eho-pilu n-eki-pilu l-aki-pilu r-aho-pilu

Generation 10

Compositional language emerges. Adaptive structure that is both learnable and expressive.

Why is there adaptation?

• Language is adapting to maximise its own

transmissibility

• Evolution from initial unlearnable random

language to learnable structured one

• Note: this is a blind process. Not the result of

intentional design by individuals. Design without designer (or biological evolution)

• Driven by bottleneck on transmission:

learners only see a subset of utterances

INTERNAL REPRESENTATION

OBSERVED UTTERANCES

INTERNAL REPRESENTATION BOTTLENECK

• In real world, language is unboundedly productive. This leads to an inevitable

poverty of the stimulus (i.e., transmission bottleneck)

• Chomsky sees this as a learning problem, suggesting the child must be born

with specific knowledge of language in order to solve it

• But now we can look at it another way: it is a challenge a culturally evolving

language must meet. Language structure is an adaptive response to this challenge, allowing language to be reliably transmitted despite the poverty of the stimulus

• The design-like features of language are not a result of us adapting to

language, but rather language adapting to us.

The poverty of the stimulus

• These results are not dependent on having chains of individuals
• Same results appear to happen with dyads, and populations with multiple

speakers per generation

• Look at more flexible, continuous meanings - semantics also adapts (Matthews, Kirby

& Cornish, in prep)

• Demonstrate evolution from iconic to arbitrary structured signals (Theisen,

Oberlander & Kirby, 2009)

• Look at evolution of signals alone (Cornish, Christiansen & Kirby, in prep)
• Emergence of phonemic structure as adaptation to transmission (work with Del

Giudice, Padden, Verhoef, de Boer)

Ongoing experiments

The role of cultural evolution in biolinguistics

• We need to recognise that the link between

individual cognition is mediated by a process that does real adaptive work

• Casts doubt on some foundational

assumptions:

• Can’t infer properties of UG directly from

language universals

• Genes underpinning our faculty for

language less likely to be specific to that faculty

Universal properties

• f individual cognition

Universal properties

• f language

Genes “for” language Social interaction / cultural evolution

?

Cultural evolution: implications for understanding the human language faculty and its evolution

Kenny Smith1,* and Simon Kirby2

1Cognition and Communication Research Centre, Division of Psychology, Northumbria University,

Northumberland Building, Northumberland Road, Newcastle NE1 8ST, UK

2Language Evolution and Computation Research Unit, School of Philosophy, Psychology and Language

Sciences, University of Edinburgh, Dugald Stewart Building, 3 Charles Street, Edinburgh, EH8 9AD, UK

• Phil. Trans. R. Soc. B (2008) 363, 3591–3603

doi:10.1098/rstb.2008.0145 Published online 19 September 2008

The impact of culture on biological evolution

• Smith & Kirby (2008) investigate how culture affects biological evolution of

language faculty using mathematical model

• Model:

Genes change learners’ biases towards different possible languages Languages evolve culturally in populations of learners through iterated learning Implement natural selection of individuals based on how well they communicate

• Question: will mutants with stronger linguistic biases invade a population with

weak biases?

Shielding

• Counter-intuitive result:
• Strength of linguistic constraints/biases has no effect
• Cultural evolution “amplifies” our predispositions
• The strength of our innate constraints is shielded from the view of natural

selection

• If strong constraints need to be maintained against mutation, any innate

contributions must either be weak, or not specific to language

So what’s left for biological evolution?

• Still left with puzzle: why are humans uniquely linguistic?
• Iterated learning models suggest where to look for an answer:

Not because of specific innate knowledge of language, but because of specific preadaptations for cultural transmission

• What is assumed in all the models of iterated learning?
• A capacity to infer meanings while learning and a capacity to learn complex

sequential signals (cf. musical protolanguage)

• Ongoing work with James Thomas modelling hypothesis that these both

might arise from self-domestication

Conclusions

• We need to take into account all of the

adaptive systems implicated in the emergence of language, and their interactions

• Evolutionary processes set the scene for a

culturally transmitted system pairing complex signals with meanings

• Iterated learning then takes this and delivers

adaptive linguistic structure without requiring hard-coding of innate constraints

CULTURAL TRANSMISSION INDIVIDUAL LEARNING

LANGUAGE

BIOLOGICAL EVOLUTION

Thanks to all at the LEC, Edinburgh: www.ling.ed.ac.uk/lec