Many agent-oriented programming languages are based on the Prolog-like logical goal reduction approach where rules are used to reduce, in a depth-first way, a selected goal. The ability of agents to change between goals means that such languages often overlay the basic computational engine with a mechanism for dynamically changing which goal is selected. Our approach is different. The basic computational approach we use is that of model building for logical formulae, but the underlying formulae are temporal. This allows us to capture the dynamic nature of the agent explicitly. In addition, the temporal basis provides us with ways of having multiple active ‘goals ’ and being able to achieve several at once. As in most agent-oriented languages deliberation is used to choose between goals when not all can be satisfied at once. This basic execution of temporal formulae provides us with the foundation for agent programming. In order to deal with multi-agent systems in an equally straightforward way we also incorporate a very simple, but flexible, model of organisational structuring. These two aspects provide the core of the language implemented. There are, however, many extensions that have been proposed, some of which have been implemented, and all of which are mentioned in this article. These include varieties of agent belief, resourcebounded reasoning, the language’s use as a coordination language, and the use of contextual constraints.

Abstract. In ambient intelligent systems, monitoring of a human could consist of more complex tasks than merely identifying whether a certain value of a sensor is above a certain threshold. Instead, such tasks may involve monitoring of complex dynamic interactions between human and environment. In order to enable such more complex types of monitoring, this paper presents a generic agent-based framework. The framework consists of support on various levels of system design, namely: (1) the top level, including the interaction between agents, (2) the agent level, providing support on the design of individual agents, and (3) the level of monitoring complex dynamic behaviour, allowing the specification of the aforementioned complex monitoring properties within the agents. The approach is exemplified by a large case study concerning the assessment of driving behaviour, and is applied to two smaller cases as well (concerning fall detection of elderly, and assistance of naval operations, respectively), which are briefly described. These case studies have illustrated that the presented framework enables developers within ambient intelligence to build systems with more expressiveness regarding their monitoring focus. Moreover, they have shown that the framework is easy to use and applicable in a wide variety of domains.

.... a conscious mental and usually purposive process aimed at the self-observation and reporting of conscious inner thoughts. Introspection relies upon thinking, reasoning, and examining one's own thoughts, and is contrasted with extrospection, the observation of things external to one's self. Introspection is in general used synonymously with selfreflection. In Computer Science, reflection is usually understood as the process by which a computer program can observe and modify its own structure and behavior. Reflection, as discussed in (Costantini, 2002) can take a variety of forms according to the underlying programming paradigm, but in essence it can be seen as the act of introspecting (upward reflection) and, symmetrically, of resuming normal operation (downward reflection). In Computer Science there is instead no commonly-agreed definition of introspection. It is interesting to notice that philosophy provides, since Locke, an “observational model ” of introspection where introspective capacity enables us to observe the inner world just as perceptual capacity enables us to observe the outer world. In analogy to philosophy, in this paper we shall understand introspection as the ability to create and access arepresentation of the object-level knowledge and reasoning processes and to be able to perform metareasoning based on this representation that can be considered as a (partial)