Nature-Inspired Coordination Models: Current Status and Future Trends

Coordination models and languages are meant to provide abstractions and mechanisms to harness the space of interaction as one of the foremost sources of complexity in computational systems. Nature-inspired computing aims at understanding the mechanisms and patterns of complex natural systems in order to bring their most desirable features to computational systems. Thus, the promise of nature-inspired coordination models is to prove themselves fundamental in the design of complex computational systems|such as intelligent, knowledge-intensive, pervasive, adaptive, and self-organising ones. In this paper, we survey the most relevant nature-inspired coordination models in the literature, focussing in particular on tuple-based models, and foresee the most interesting research trends in the field

Logic-based Technologies for Intelligent Systems: State of the Art and Perspectives

Together with the disruptive development of modern sub-symbolic approaches to artificial intelligence (AI), symbolic approaches to classical AI are re-gaining momentum, as more and more researchers exploit their potential to make AI more comprehensible, explainable, and therefore trustworthy. Since logic-based approaches lay at the core of symbolic AI, summarizing their state of the art is of paramount importance now more than ever, in order to identify trends, benefits, key features, gaps, and limitations of the techniques proposed so far, as well as to identify promising research perspectives. Along this line, this paper provides an overview of logic-based approaches and technologies by sketching their evolution and pointing out their main application areas. Future perspectives for exploitation of logic-based technologies are discussed as well, in order to identify those research fields that deserve more attention, considering the areas that already exploit logic-based approaches as well as those that are more likely to adopt logic-based approaches in the future

The SLIM (Social learning for the integrated management and sustainable use of water at catchment scale) Final Report

Background: SLIM stands for 'Socuak Learning for the Integrated Management and Sustainable Use of Water at Catchment Scale'. It is a multi-country research project funded by the European Commission (DG RESEARCH - 5th Framework Programme for research and technological development, 1998-2002). Its main theme is the investigation of the socio-economic aspects of the sustainable use of water. Within this theme, its main focus of interest lies in understanding the application of social learning as a conceptual framework, an operational principle, a policy instrument and a process of systemic change

Interim research assessment 2003-2005 - Computer Science

This report primarily serves as a source of information for the 2007 Interim Research Assessment Committee for Computer Science at the three technical universities in the Netherlands. The report also provides information for others interested in our research activities

Model-Driven Development of Aspect-Oriented Software Architectures

The work presented in this thesis of master is an approach that takes advantage of the Model-Driven Development approach for developing aspect-oriented software architectures. A complete MDD support for the PRISMA approach is defined by providing code generation, verification and reusability properties.Pérez Benedí, J. (2007). Model-Driven Development of Aspect-Oriented Software Architectures. http://hdl.handle.net/10251/12451Archivo delegad

Twenty years of coordination technologies: State-of-the-art and perspectives

Since complexity of inter- and intra-systems interactions is steadily increasing in modern application scenarios (e.g., the IoT), coordination technologies are required to take a crucial step towards maturity. In this paper we look back at the history of the COORDINATION conference in order to shed light on the current status of the coordination technologies there proposed throughout the years, in an attempt to understand success stories, limitations, and possibly reveal the gap between actual technologies, theoretical models, and novel application needs

Context-Adaptive Coordination of Pervasive Services by Interpreting Models during Runtime

[EN] One of the most important goals of pervasive systems is to help users in their daily life by automating their behaviour patterns. To achieve this, pervasive services must be dynamically coordinated, executed and adapted to context according to user behaviour patterns. In this work, we propose a model-driven solution to meet this challenge. We propose a task model and a context ontology to design context-adaptive coordination of services at a high level of abstraction. This design facilitates the coordination analysis at design time and is also reused at runtime. We propose a software architecture that interprets the models at runtime in order to coordinate the service execution that is required to support user behaviour patterns. This coordination is done in a context-adaptive way and decoupled from service implementation. This approach makes the models the only representation of service coordination, which facilitates the maintenance and evolution of the executed service coordination after deployment.This work has been developed with the support of (a) MICINN under the project EVERYWARE TIN2010-18011 and (b) MITYC under the project LIFEWEAR TSI-020400-2010-100 co-funded with ERDF.Serral Asensio, E.; Valderas Aranda, PJ.; Pelechano Ferragud, V. (2013). Context-Adaptive Coordination of Pervasive Services by Interpreting Models during Runtime. Computer Journal. 56(1):87-114. https://doi.org/10.1093/comjnl/bxs019S8711456