Talking nets: a multiagent connectionist approach to communication and trust between individuals

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.