Geekspeak的社会级联及其对社会认知系统的影响
Understanding the Social Cascading of Geekspeak and the Upshots for Social Cognitive Systems
摘要：
除了群体机器人之外，当前机器-人和机器-机器学习和交互机制的相当大的份额正在开发，并由基于代理的计算机模拟、博弈论模型或基于二元通信模式的机器人实验的结果提供。然而，在现实生活中，人类同样频繁地在群体中交流，并根据从多个单一来源累积收集的信息获得知识和做出决策。这些属性应考虑到自主人工认知系统的设计解释与学习从一个以上的接触或“邻居”。为此，可以从严格的科学方法论应用于人类和社会现象的研究中收集到重要的实际意义，例如发现现实的创造力潜力跨度，或“曝光阈值”，在此之后，新信息可以被认知代理人接受。将介绍一个分析微博服务中新词社会传播的项目的结果。从本地，低层次的互动和信息流之间的代理发明和模仿离散的词汇，我们的目标是描述更多的全球系统秩序和动态的出现过程中，使用复杂性科学的最新方法。无论是为了模仿它们，还是为了“增强”它们，从复杂性科学方法中收集到的人类社会和人文行为的参数应该随后作为机器人和人机交互领域的参考点。
英文摘要：
Barring swarm robotics, a substantial share of current machine-human and machine-machine learning and interaction mechanisms are being developed and fed by results of agent-based computer simulations, game-theoretic models, or robotic experiments based on a dyadic communication pattern. Yet, in real life, humans no less frequently communicate in groups, and gain knowledge and take decisions basing on information cumulatively gleaned from more than one single source. These properties should be taken into consideration in the design of autonomous artificial cognitive systems construed to interact with learn from more than one contact or 'neighbour'. To this end, significant practical import can be gleaned from research applying strict science methodology to human and social phenomena, e.g. to discovery of realistic creativity potential spans, or the 'exposure thresholds' after which new information could be accepted by a cognitive agent. The results will be presented of a project analysing the social propagation of neologisms in a microblogging service. From local, low-level interactions and information flows between agents inventing and imitating discrete lexemes we aim to describe the processes of the emergence of more global systemic order and dynamics, using the latest methods of complexity science. Whether in order to mimic them, or to 'enhance' them, parameters gleaned from complexity science approaches to humans' social and humanistic behaviour should subsequently be incorporated as points of reference in the field of robotics and human-machine interaction.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
