Ambiguity Preference and Context Learning in Uncertain Signaling

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Abstract

Lexical ambiguity is present in many natural languages, but ambiguous words and phrases do not seem to be advantageous. Therefore, the presence of ambiguous words in natural language warrants explanation. We justify the existence of ambiguity from the perspective of the context dependence. The main contribution of the paper is that we constructed a context learning process such that the interlocutors can infer opponent’s private belief from the conversation. A sufficient condition is proved to show if the learning can be successful. Furthermore, we investigate when the learning fails, how the interlocutors choose among degrees of ambiguous expressions through an adaptive learning.

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APA

Tang, L. (2020). Ambiguity Preference and Context Learning in Uncertain Signaling. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12061 LNAI, pp. 201–218). Springer. https://doi.org/10.1007/978-3-030-44638-3_13

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