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

Abstract

How is information transmitted in a group? A multi-agent connectionist model is proposed that combines features of standard recurrent models to simulate the process of information uptake, integration and memorization within individual agents, with novel aspects that simulate the communication of beliefs and opinions between agents. A crucial aspect in belief updating based on information from other agents is the trust in the information provided, implemented as the consistency with the receiving agents' existing beliefs. Trust leads to a selective propagation and thus filtering out of less reliable information, and implements Grice's (1975) maxims of quality and quantity in communication. By studying these communicative aspects within the framework of standard models of information processing, the unique contribution of communicative mechanisms beyond intra-personal factors 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. TRUST Connectionist Model of Communication 3Cognition is not limited to the mind of an individual agent, but involves interactions with other minds. A full understanding of human thinking thus requires a deeper insight of its social origin. Sociologists and developmental psychologists have long noted that most of our knowledge of reality is the result of a social construction and communication rather than of individual observation. Economists emphasize that effective knowledge management and learning is an organizational phenomenon that determines enterprise's success or failure (Senge, 1990).Collective behaviors have a long evolutionary past, as biologists and computer scientists have built models that demonstrate how collectives of simple agents, such as ant colonies, bee hives, or flocks of birds, can process complex information more effectively than single agents facing the same tasks (Bonabeau et al., 1999).Social psychologists too have studied cognition at the group level, using laboratory experiments to document various biases and shortcomings of collective intelligence. Research has revealed that we often fall prey to biases and simplistic stereotypes about other groups, and that many of these distorted representations are emergent properties of the cognitive dynamics in single or multiple minds. Some of these biased processes are illusory correlation or the creation of an unwarranted association between a group and undesirable characteristics, accentuation of differences between groups, subtyping of deviant members (for a review see Van Rooy, Van Overwalle, Vanhoomissen, Labiouse & French, 2004) and the communication of stereotypes (e.g., Lyons & Kashima, 1993). With respect to processes within a group, different types of social dynamics lead to a less than optimal performance. These include conformity and polarization which move a group as a whole towards more extreme opinions (Ebbesen & Bowers, 1974;Mackie & ...

Self-organization in Communicating Groups: The Emergence of Coordination, Shared References and Collective Intelligence

“…In the connectionist simulation to which I contributed [Van Overwalle & Heylighen, 2006], the naming game experiment was repeated with somewhat different assumptions about the agents' learning mechanism and mode of communication than the original experiment, but with essentially the same results. This illustrates once again how strong the power of self-organizing alignment is for communicating groups.…”

“…Another classic example of such local alignment is cultural homogeneization, where people in a frequently interacting group will tend to converge in their dialects, beliefs, attitudes and habits, while diverging from neighboring groups with which there is less interaction [Axelrod, 1997;Van Overwalle & Heylighen, 2006]. This is the origin of relatively homogeneous cultural groups such as languages, religions, and ethnicities.…”

Determination of potential of student on the basis of data about result and psychological comfort of education

“…A better approach is to closely integrate simulation and empirical observation, so that we can try to find more fine-grained correlations between the behavior of the simulation model and the one of real individuals [e.g. Van Overwalle & Heylighen, 2006]. One way to apply this method to test the propagation depth model will be elaborated in the appendix.…”

Developing an agent-based model on how different individuals solve complex problems

“…These other areas include leadership (Gigliotta, Miglino & Parisi, 2007), decision-making (Wilson, 2007;Sun & Naveh, 2004), teamwork (Overwalle & Heylighen, 2006), sociology (Sallach & Macal, 2001;Gilbert & Abbot, 2005;Todd, Billari & Simao, 2005) and cognition and emotion (Bandura, 2001;Gratch & Marsella, 2005).…”