自动提取多智能体通信中的语义规则，让自动生成的对话可解释。
Automated Semantic Rules Detection (ASRD) for Emergent Communication Interpretation
- 基于Lewis游戏数据，自动识别智能体通信中的模式规律。
- 将通信内容与输入数据属性关联，提升语言可理解性。
- 适合研究自组织通信机制或可解释人工智能的学者。
多智能体系统中的涌现通信研究关注自主智能体如何在无明确编程的情况下独立发展通信策略，并适应不同环境。然而，极少有研究关注涌现语言的可解释性。本文提出自动化语义规则检测（ASRD）算法，该算法从两个不同数据集上训练的智能体在Lewis游戏中交换的消息中提取相关模式。ASRD通过将提取出的模式与输入数据的具体属性建立联系，显著简化了后续分析，有助于理解智能体间的沟通逻辑。
原文摘要 · Abstract (English)
The field of emergent communication within multi-agent systems examines how autonomous agents can independently develop communication strategies, without explicit programming, and adapt them to varied environments. However, few studies have focused on the interpretability of emergent languages. The research exposed in this paper proposes an Automated Semantic Rules Detection (ASRD) algorithm, which extracts relevant patterns in messages exchanged by agents trained with two different datasets on the Lewis Game, which is often studied in the context of emergent communication. ASRD helps at the interpretation of the emergent communication by relating the extracted patterns to specific attributes of the input data, thereby considerably simplifying subsequent analysis.
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