Van Overwalle Frank, Heylighen Francis
Department of Psychology, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium.
Psychol Rev. 2006 Jul;113(3):606-27. doi: 10.1037/0033-295X.113.3.606.
A multiagent connectionist model is proposed that consists of a collection of individual recurrent networks that communicate with each other and, as such, is a network of networks. The individual recurrent networks simulate the process of information uptake, integration, and memorization within individual agents, and the communication of beliefs and opinions between agents is propagated along connections between the individual networks. A crucial aspect in belief updating based on information from other agents is the trust in the information provided. In the model, trust is determined by the consistency with the receiving agents' existing beliefs and results in changes of the connections between individual networks, called trust weights. These weights lead to a selective propagation and thus to the filtering out of less reliable information, and they implement H. P. Grice's (1975) maxims of quality and quantity in communication. The unique contribution of communicative mechanisms beyond intrapersonal processing of individual networks was explored in simulations of key phenomena involving persuasive communication and polarization, lexical acquisition, spreading of stereotypes and rumors, and a lack of sharing unique information in group decisions.
提出了一种多智能体连接主义模型，它由一组相互通信的个体循环网络组成，因此是一个网络的网络。个体循环网络模拟个体智能体内信息的摄取、整合和记忆过程，智能体之间信念和观点的交流沿着个体网络之间的连接进行传播。基于来自其他智能体的信息进行信念更新的一个关键方面是对所提供信息的信任。在该模型中，信任由与接收智能体现有信念的一致性决定，并导致个体网络之间连接的变化，称为信任权重。这些权重导致选择性传播，从而过滤掉不太可靠的信息，并且它们在通信中实现了H. P. 格赖斯（1975）的质量和数量准则。在涉及说服性沟通和两极分化、词汇习得、刻板印象和谣言传播以及群体决策中缺乏共享独特信息等关键现象的模拟中，探索了超越个体网络内部处理的交际机制的独特贡献。
