Behaviour support technology assists people in organising their daily activities and changing their behaviour. A fundamental notion underlying such supportive technology is that of compliance with behavioural norms: do people indeed perform the desired behaviour? Existing technology employs a rigid implementation of compliance: a norm is either satisfied or not. In practice however, behaviour change norms are less strict: E.g., is a new norm to do sports at least three times a week complied with if it is occasionally only done twice a week? To address this, in this paper we formally specify probabilistic norms through a variant of feature diagrams, enabling a hierarchical decomposition of the desired behaviour and its execution frequencies. Further, we define a new notion of probabilistic norm compliance using a formal hypothesis testing framework. We show that probabilistic norm compliance can be used in a real-world setting by implementing and evaluating our semantics with respect to an existing daily behaviour dataset.

Ethics by Design concerns the methods, algorithms and tools needed to endow autonomous agents with the capability to reason about the ethical aspects of their decisions, and the methods, tools and formalisms to guarantee that an agent's behavior remains within given moral bounds. In this context some questions arise: How and to what extent can agents understand the social reality in which they operate, and the other intelligences (AI, animals and humans) with which they co-exist? What are the ethical concerns in the emerging new forms of society, and how do we ensure the human dimension is upheld in interactions and decisions by autonomous agents?. But overall, the central question is: "Can we, and should we, build ethically-aware agents?" This paper presents initial conclusions from the thematic day of the same name held at PRIMA2017, on October 2017.

Behaviour support technology is aimed at assisting people in organizing their Activities of Daily Living (ADLs). Numerous frameworks have been developed for activity recognition and for generating specific types of support actions, such as reminders. The main goal of our research is to develop a generic formal framework for representing and reasoning about ADLs and their temporal relations. This framework should facilitate modelling and reasoning about 1) durative activities, 2) relations between higher-level activities and subactivities, 3) activity instances, and 4) activity duration. In this paper we present a temporal logic as an extension of the logic TPTL for specification of real-time systems. Our logic TPTL_bih is defined over Behaviour Identification Hierarchies (BIHs) for representing ADL structure and typical activity duration. To model execution of ADLs, states of the temporal traces in TPTL_bih comprise information about the start, stop and current execution of activities. We provide a number of constraints on these traces that we stipulate are desired for the accurate representation of ADL execution, and investigate corresponding validities in the logic. To evaluate the expressivity of the logic, we give a formal definition for the notion of Coherence for (complex) activities, by which we mean that an activity is done without interruption and in a timely fashion. We show that the definition is satisfiable in our framework. In this way the logic forms the basis for a generic monitoring and reasoning framework for ADLs.