Intention Recognition with Evolution Prospection and Causal Bayesian Networks

We describe a novel approach to tackle intention recognition, by combining dynamically configurable and situation-sensitive Causal Bayes Networks plus plan generation techniques. Given some situation, such networks enable the recognizing agent to come up with the most likely intentions of the intending agent and, in case of having to make a quick decision, focus on the important ones. The combination with plan generation provides a significant method to guide the recognition process with respect to hidden actions and unobservable effects, to confirm or disconfirm likely intentions. The absence of this articulation is a main drawback of the approaches using Bayes Networks solely, due to the combinatorial problem they encounter. We explore and exemplify its application, in the Elder Care context, of the ability to perform Intention Recognition and of wielding Evolution Prospection methods to help the Elder achieve its intentions.