Robustness of policies in Constrained Markov Decision Processes

We consider the optimization of finite-state, finite-action Markov Decision processes, under con-straints. Cost and constraints are of the discounted type. We introduce a new method for investigating the continuity and robustness of the optimal cost and the optimal policy under changes in the constraints. This method is also applicable for other cost criteria such as finite horizon and infinite horizon average cost

Emotion-awareness for intelligent vehicle assistants: a research agenda

EVA1 is describing a new class of emotion-aware autonomous systems delivering intelligent personal assistant functionalities. EVA requires a multi-disciplinary approach, combining a number of critical building blocks into a cybernetics systems/software architecture: emotion aware systems and algorithms, multimodal interaction design, cognitive modelling, decision making and recommender systems, emotion sensing as feedback for learning, and distributed (edge) computing delivering cognitive services