object Lexicon extends Serializable
Companion object to Lexicon containing alternative constructors and generation functions.
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def
apply(matrix: Array[Array[Double]]): Lexicon
Constructor for Lexicon.
Constructor for Lexicon.
- matrix
A 2-dimensional array representation of a graded lexicon. Rows represent the vocabulary, columns represent the context.
- returns
A (graded) lexicon.
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def
apply(matrix: Vector[Vector[Double]]): Lexicon
Constructor for Lexicon.
Constructor for Lexicon.
- matrix
A 2-dimensional vector representation of a graded lexicon. Rows represent the vocabulary, columns represent the context.
- returns
A (graded) lexicon.
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def
asBlokpoelEtalListener(lexicon: Lexicon, n: Int): Lexicon
Returns a transformation of lexicon corresponding to a
nth order listener as defined by Blokpoel et al.Returns a transformation of lexicon corresponding to a
nth order listener as defined by Blokpoel et al. (2020).- lexicon
The lexicon to be transformed.
- n
The order of pragmatic reasoning.
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def
asBlokpoeletalSpeaker(lexicon: Lexicon, n: Int): Lexicon
Returns a transformation of this lexicon corresponding to a
nth order speaker as defined by Blokpoel et al.Returns a transformation of this lexicon corresponding to a
nth order speaker as defined by Blokpoel et al. (2020).- lexicon
The lexicon to be transformed.
- n
The order of pragmatic reasoning.
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def
asFrankGoodmanListener(lexicon: Lexicon, n: Int): Lexicon
Returns a transformation of this lexicon corresponding to a
nth order listener as defined by Frank and Goodman (2012).Returns a transformation of this lexicon corresponding to a
nth order listener as defined by Frank and Goodman (2012).- lexicon
The lexicon to be transformed.
- n
The order of pragmatic reasoning.
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def
asFrankGoodmanSpeaker(lexicon: Lexicon, n: Int): Lexicon
Returns a transformation of this lexicon corresponding to a
nth order speaker as defined by Frank and Goodman (2012).Returns a transformation of this lexicon corresponding to a
nth order speaker as defined by Frank and Goodman (2012).- lexicon
The lexicon to be transformed.
- n
The order of pragmatic reasoning.
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def
asFrankeDegenListener(lexicon: Lexicon, n: Int): Lexicon
Returns a transformation of lexicon corresponding to a
nth order listener as defined by Franke and Degen (2016).Returns a transformation of lexicon corresponding to a
nth order listener as defined by Franke and Degen (2016).- lexicon
The lexicon to be transformed.
- n
The order of pragmatic reasoning.
-
def
asFrankeDegenSpeaker(lexicon: Lexicon, n: Int): Lexicon
Returns a transformation of lexicon corresponding to a
nth order speaker as defined by Franke and Degen (2016).Returns a transformation of lexicon corresponding to a
nth order speaker as defined by Franke and Degen (2016).- lexicon
The lexicon to be transformed.
- n
The order of pragmatic reasoning.
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def
generateConsistentAmbiguityMapping(ambiguity: Int, vocabularySize: Int, contextSize: Int): Lexicon
Generates a lexicon that is consistent (each referent has at least 1 associated word) and has a fixed ambiguity (viz., each word is associated with ambiguity referents).
Generates a lexicon that is consistent (each referent has at least 1 associated word) and has a fixed ambiguity (viz., each word is associated with ambiguity referents).
- ambiguity
The number of referents each signal refers to (ranging from 0 to contextSize).
- vocabularySize
The size of the vocabulary.
- contextSize
The size of the context.
- returns
A lexicon.
- Exceptions thrown
scala.IllegalArgumentExceptionwhencontextSize<vocabularySize.- Note
Ambiguity <= 0 generates the same type of lexicon as ambiguity = 1, and ambiguity > contextSize generates a lexicon of ambiguity = contextSize.
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def
generateRandomBinaryLexicon(probability: Double, vocabularySize: Int, contextSize: Int): Lexicon
Generates a randomized binary lexicon (i.e., each word-referent pair has
probabilityto be 1.0).Generates a randomized binary lexicon (i.e., each word-referent pair has
probabilityto be 1.0).- probability
The density parameter ranging from 0 to 1.
- vocabularySize
The size of the vocabulary.
- contextSize
The size of the context.
- returns
A randomly generated lexicon.
- Note
When probability is below 0 this returns an empty lexicon, when it is above 1 result a full lexicon.
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Language Agents Simulation framework
For detailed documentation on using the framework please see the README.md file at the Github repository at https://github.com/markblokpoel/lanag-core.