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Abstract
The evolution of language implies the parallel evolution of an ability to respond appropriately to signals (language understanding) and an ability to produce the appropriate signals in the appropriate circumstances (language production). When linguistic signals are produced to inform other individuals, individuals that respond appropriately to these signals may increase their reproductive chances but it is less clear what the reproductive advantage is for the language producers. We present simulations in which populations of neural networks living in an environment evolve a simple language with an informative function. Signals are produced to help other individuals categorize edible and poisonous mushrooms, in order to decide whether to approach or avoid encountered mushrooms. Language production, while not under direct evolutionary pressure, evolves as a byproduct of the independently evolving perceptual ability to categorize mushrooms.BibTexKeywords: Language evolution, genetic algorithm, artificial life, symbol grounding
@article{cangelosi98theEmergence,
author={A. Cangelosi and D. Parisi},
title={The emergence of a language in an evolving population of neural networks},
journal={Connection Science},
year={1998},
volume={10},
number={2},
pages={83-97},
doi={10.1080/095400998116512},
url={http://www.isrl.uiuc.edu/~amag/langev/paper/cangelosi98theEmergence.html},
keywords={Language evolution, genetic algorithm, artificial life, symbol grounding}
}
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