Compositional Signaling in a Complex World
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Natural languages are compositional in that the meaning of complex expressions depends on those of the parts and how they are put together. Here, I ask the following question: why are languages compositional? I answer this question by extending Lewis–Skyrms signaling games with a rudimentary form of compositional signaling and exploring simple reinforcement learning therein. As it turns out: in complex worlds, having compositional signaling helps simple agents learn to communicate. I am also able to show that learning the meaning of a function word, once meanings of atomic words are known, presents no difficulty.
KeywordsSignaling games Compositionality Reinforcement learning Evolution Negation
I would like to thank the organizers and participants at IDAS’14 and especially Stefano Demichelis and Roland Muehlenbernd for stimulating discussion. An earlier version was presented at a workshop on Knowledge, Argumentation, and Games in Amsterdam. For discussion there, I thank especially Michael Franke and Alexandru Baltag. Jeffrey Barrett, Johan van Benthem, Thomas Icard, Chris Potts, Carlos Santana, Brian Skyrms, and Michael Weisberg have provided helpful comments on earlier versions of this paper as did three anonymous referees for this journal.
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