提出新模型让信号接收者真正理解组合信息。
Compositional Understanding in Signaling Games
- 设计极简与泛化两类接收者，只学消息原子成分。
- 接收者能保留各成分独立信息，不因部分丢失而全忘。
- 适合研究语言习得与组合性认知的学者参考。
标准信号博弈模型中的接收者难以学习组合信息：即使信号发送者传递了组合式消息，接收者也无法进行组合理解。当某一消息成分的信息丢失或遗忘时，其他成分的信息也会随之消失。本文构建了两种新型信号博弈模型，使真正的组合理解得以演化。提出两种新模型：一种是仅从信号原子成分学习的极简接收者，另一种是利用所有可用信息的泛化接收者。这些模型在多数方面比以往方案更简单，且使接收者能够从消息的原子组件中学习。
原文摘要 · Abstract (English)
Receivers in standard signaling game models struggle with learning compositional information. Even when the signalers send compositional messages, the receivers do not interpret them compositionally. When information from one message component is lost or forgotten, the information from other components is also erased. In this paper I construct signaling game models in which genuine compositional understanding evolves. I present two new models: a minimalist receiver who only learns from the atomic messages of a signal, and a generalist receiver who learns from all of the available information. These models are in many ways simpler than previous alternatives, and allow the receivers to learn from the atomic components of messages.
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