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MoLE (version 1.0.0)

Modeling Language Evolution

Description

Model for simulating language evolution in terms of cultural evolution (Smith & Kirby (2008) ; Deacon 1997). The focus is on the emergence of argument-marking systems (Dowty (1991) , Van Valin 1999, Dryer 2002, Lestrade 2015a), i.e. noun marking (Aristar (1997) , Lestrade (2010) ), person indexing (Ariel 1999, Dahl (2000) , Bhat 2004), and word order (Dryer 2013), but extensions are foreseen. Agents start out with a protolanguage (a language without grammar; Bickerton (1981) <10.17169/langsci.b91.109>, Jackendoff 2002, Arbib (2015) ) and interact through language games (Steels 1997). Over time, grammatical constructions emerge that may or may not become obligatory (for which the tolerance principle is assumed; Yang 2016). Throughout the simulation, uniformitarianism of principles is assumed (Hopper (1987) , Givon (1995) , Croft (2000), Saffran (2001) , Heine & Kuteva 2007), in which maximal psychological validity is aimed at (Grice (1975) , Levelt 1989, Gaerdenfors 2000) and language representation is usage based (Tomasello 2003, Bybee 2010). In Lestrade (2015b) , Lestrade (2015c) , and Lestrade (2016) ), which reported on the results of preliminary versions, this package was announced as WDWTW (for who does what to whom), but for reasons of pronunciation and generalization the title was changed.

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Version

Install

install.packages('MoLE')

Monthly Downloads

190

Version

1.0.0

License

GPL-2

Maintainer

Sander Lestrade

Last Published

July 3rd, 2017

Functions in MoLE (1.0.0)

CHECKSUCCESS

Determine expected communicative success
DECOMPOSE

Decompose words into morphemes
ALLNAS

NA vector identification
ANALYZE

Determine sentence constituents
FMATCH

Compare forms
FORMS

Generate forms
CANDIDATESCORE

Score candidate expressions
CHECKMARKER

Inspect developmental history
FOUND

Found population
FREQUPDATE

Update usage numbers
NOUNMORPHOLOGY

Interpret nominal morphology
NOUNS

Generate nominal lexicon
RESCALE

Rescale vector values
RUN

Run simulation
FIRSTINFIRSTOUT

Order constituents by activation
FIRSTSPEAKER

Create founding agent
MAX

Find maximum value
MULTIRUN

Run several lineages
SUCCESS

Determine communicative success
SITUATION

Create situational context
SELECTACTOR

Find actor expression
SEMUPDATE

Update lexicon
VERBFINAL

Put verb final
VERBMORPHOLOGY

Interpret verbal morphology
PERSONUPDATE

Adjust person value
PREPARE

Prepare a proposition for production
PROCREATE

Generate new generation of agents
DIE

Kill agents
EROSION

Word erosion
FUSE

Fuse words
GENERALIZE

Apply linguistic generalizations
PRODUCE

Produce utterance
TOPICCOPY

Make anaphoric copy of topic
TOPICFIRST

Put topic in first position
ACTOR

Determine actor role
AGENTFIRST

Actor argument first
GROUP

Group words into constituents
HISTORY

Inspect language-change history
INTERPRET.INT

Develop an interpretation
INTERPRET

Interpret utterance
REDUCE

Reduce length of expressions
REFCHECK

Check referential capacity
TURN

Organize communicative turn
MoLE-package

MoLE
NOUNDESEMANTICIZATION

Bleach word meaning
PROPOSITION

Develop initial proposition
PROTOINTERPRETATION

Develop interpretation
TYPEMATCH

Determine role qualification
WORDORDER

Use word order for interpretation
world

Model parameters
SUMMARY

Summarize simulation results
TALK

Let agents talk
VERBS

Generate verbal lexicon
VMATCH

Compare vectors