Crowd simulation can play a crucial role when it comes to the design of Smart Environments. Crowd simulation can give insights on the flow of pedestrian in particular facilities and explore the interplay between ambient intelligence deployments and users. Most researchers develop crowd simulations using commercial game engines built with the editors they usually provide. This prevents a deeper experimentation with the problems of crowd simulation and enforces to stick to the development paradigm of the tool. As a consequence, it couples the scientific experimentation that produces the crowd model with the actual construction of the simulation tool. Besides, a crowd simulation may require more resources than those available to the scientist. A solution would be to conceive crowd simulation as a service that, on the one hand, it allowed scientists to experiment with the latest advances without the burden of installing elements or acquiring expensive computational resources; and, on the other hand, it enabled developers to evolve the tool in a scalable way. The contribution of the paper is a framework that enables the “simulation as a service” approach for crowd simulations when they are run with a 3D representation. As a proof of concept, the paper illustrates how crowd simulations can be used to generate datasets that allow studying the deployment of sensors in a large facility.

Ambient Assisted Living (AAL) pursues providing an autonomous and satisfactory life to people through technology, independently of their actual conditions.Its developments usually require testing protoypes with real users in Living Labs (LL).This makes projects expensive.Virtual LLs (VLLs) try to address theses issues by using simulations for requirements elicitation and the initial testing of solutions.These simulations frequently require considering social aspects, e.g.relationships, culture, or decision making.These are recurrent and quite applicationindependent aspects for AAL.Our work proposes social properties as patterns that represent these aspects and that can be plugged-in in simulations.The knowledge for these properties is extracted following the Activity Theory (AT) paradigm from Social Sciences.Their specification uses models and transformations (e.g. to generate other models or code) following Model-Driven Engineering (MDE) practices.This faciliates their understading and use in simulation development.A case study on AAL for ageing illustrates the approach.

In some areas of software engineering research, there are several metamodels claiming to capture the main issues. Though it is profitable to have variety at the beginning of a research field, after some time, the diversity of metamodels becomes an obstacle, for instance to the sharing of results between research groups. To reach consensus and unification of existing metamodels, metamodel-driven software language engineering can be applied. This paper illustrates an application of software language engineering in the agent-oriented software engineering research domain. Here, we introduce a relatively generic agent-oriented metamodel whose suitability for supporting modeling language development is demonstrated by evaluating it with respect to several existing methodology-specific metamodels. First, the metamodel is constructed by a combination of bottom-up and top-down analysis and best practice. The concepts thus obtained and their relationships are then evaluated by mapping to two agent-oriented metamodels: TAO and Islander. We then refine the metamodel by extending the comparisons with the metamodels implicit or explicit within five more extant agent-oriented approaches: Adelfe, PASSI, Gaia, INGENIAS, and Tropos. The resultant FAML metamodel is a potential candidate for future standardization as an important component for engineering an agent modeling language.

Requirements elicitation and analysis is intended to gain knowledge about customers' needs and the environment of a software system. Requirements not only commonly deal with business processes and their data but also with the motivation behind these activities, the social structures that forge them, and previous design decisions. Recent studies show that the intentional and social concepts of agent-oriented software engineering (AOSE) could be used for the analysis of these aspects. Nevertheless, even having specialized modeling primitives for these requirements is not sufficient for their elicitation. Specialized analysis techniques are also required, but this is commonly overlooked by agent-oriented methodologies. This paper aims to provide the needed modeling primitives and support by means of the theoretical and methodological foundation of a social sciences framework, the activity theory, and its activity checklist. They inspire our requirements elicitation guide (REG) for AOSE. The REG contains the expert knowledge that developers need to grasp information about their multiagent systems, human environments, and their mutual influences. This knowledge takes the form of requirements described as diagrams in a proper modeling language. The REG is applied in a process with the corresponding support tool. In this way, the REG guides requirements elicitation and increases the productivity with the use of templates for a wide range of requirements. These elements have been validated with several case studies. Two of them appear as part of this paper.