AI 中文总结
本研究开发智能体模型，通过蒙特卡洛模拟探究网络上智能体交互的共同基础形成与演化，揭示不同交互情境会导致全球共同基础形成、分裂或完全丧失等现象，凸显数学模型研究文化动态微宏观关联的潜力。
AI 中文摘要
群体中共享共同基础的存在对集体行动与协作至关重要，但导致共同基础在宏观层面形成与演化的微观认知及社会过程尚未得到充分理论阐释，也未被严谨探索。本研究采用形式化方法，开发了一个智能体模型，描述网络上交互的智能体之间的重复基础尝试，在涉及信息共享的交互中明确区分发送智能体与接收智能体。若干关键新特征使我们能够捕捉不同交互情境：我们允许交互结果为接受或拒绝，接收方的响应可能丢失给发送方，发送方可将这种无响应解读为接受、拒绝或介于两者之间的状态。一系列蒙特卡洛模拟揭示，不同交互情境及可用共享信息会导致不同的涌现现象，如形成全球共享共同基础、分裂为多个具有不同共同基础的集群，甚至完全丧失任何共享共同基础。本研究凸显了使用数学模型研究文化动态中微观-宏观关联的潜力，包括识别促进互动以培育全球共享共同基础出现的方式。
英文摘要
The existence of a communal common ground is vital for collective action and coordination in a population, but the micro-level cognitive and social processes that lead to the formation and evolution of common ground at the macro-level are undertheorised and have not been rigorously explored. In this work, we adopt a formal approach and develop an agent-based model that describes repeated grounding attempts between agents interacting on a network, with an explicit distinction between a sender agent and a receiver agent during an interaction involving sharing information. Several key novel features enable us to capture a range of different interaction contexts: we allow for the interaction to result in either acceptance or rejection, the receiver's response may be lost to the sender, and the sender can interpret this lack of response as either acceptance or rejection (or even something in between). A campaign of Monte Carlo simulations reveals how different interaction contexts, as well as the available information for sharing, result in different emergent phenomena, such as a global communal common ground, fragmentation into multiple clusters of differing common ground, and even the total loss of any shared common ground. This work highlights the potential for using mathematical models to study micro-macro links in cultural dynamics, including identifying ways to facilitate interactions to foster the emergence of a global communal common ground.
CommentsSubmission for a journal paper
