Proceedings of the Annual Meeting of the Cognitive Science Society

What capacities enable linguistic interaction? While severalproposals have been advanced, little progress has been made incomparing and articulating them within an integrative frame-work. In this paper, we take initial steps towards a connec-tionist framework designed to systematically compare differ-ent cognitive models of social interactions. The frameworkwe propose couples two simple-recurrent network systems(Chang, 2002) to explore the computational underpinnings ofinteraction, and apply this modeling framework to predict thesemantic structure derived from transcripts of an experimen-tal joint decision task (Bahrami et al., 2010; Fusaroli et al.,2012). In an exploratory application of this framework, wefind (i) that the coupled network approach is capable of learn-ing from noisy naturalistic input but (ii) that integration of pro-duction and comprehension does not increase the network per-formance. We end by discussing the value of looking to tra-ditional parallel distributed processing as flexible models forexploring computational mechanisms of conversation.