Interactive AI

(The FCAI research programs are currently in a ramp-up phase. More information will be updated here later.)

The goal of FCAI’s research program Interactive AI is to enable AI that people can naturally work and solve problems with, and which demonstrates the ability to better understand our goals and abilities, takes initiative more sensitively, aligns its objectives with us, and supports us. This research program contributes to FCAI research objective Understandability (objective III) by developing methods for collaborative forms of AI: the ability to infer human beliefs and abilities from observations and predicting the consequences of its actions on humans

Our main expertise is in Bayesian and reinforcement learning (RL) based models of foundational capabilities in AI-human interaction, such as, among others, theory of mind (AI infers beliefs and mental causes of human actions), causal prediction (AI predicts the consequences of its actions on humans), and value-alignment (AI adapts to inferred motivations and needs of humans). The outcomes of Interactive AI research program include generative models of human interactive behavior based on the Bayesian brain hypothesis, inference of cognitive models from data using approximate Bayesian computation, interactive modeling of user intent through RL, and RL methods for sample-efficient policy search in robotics and computational agents.

Coordinating professor: Antti Oulasvirta – antti.oulasvirta at


The groups of following professors already take part in the research program Interactive AI. The list is currently under construction. If your group is already involved and needs listing here, please contact the program coordinator.