Given that emotion is a key element of human interaction, enabling artificial agents with the ability to reason about affect is a key stepping stone towards a future in which technological agents and humans can work together while respecting ethical, moral and normative orders in society.
In this talk, the speaker will present his work on building intelligent computational agents that parsimoniously integrate both emotion and cognition. These agents are grounded in the well-established social-psychological Affect Control Theory and his recent probabilistic generalization of it, Bayesian Affect Control Theory (BayesACT).
The core idea of BayesACT is that humans are motivated in their social interactions by effective alignment: they strive for their social experiences to be coherent at a deep, emotional level with their sense of identity and general worldviews as constructed through culturally shared symbols. This effective alignment creates cohesive bonds between group members, and is instrumental for collaborations to solidify as relational group commitments. The speaker will discuss using this model in the study of online collaborative networks such as GitHub.