John Thangarajah – författare

This book constitutes the thoroughly refereed post-conference proceedings of the 10th International Workshops on Coordination, Organizations, Institutions and Norms in Agent Systems, COIN 2014. The workshops were co-located with AAMAS 2014, held in Paris, France, in May 2014, and with PRICAI 2014, held in Gold Coast, QLD, Australia, in December 2014.The 16 full papers were carefully reviewed and selected for inclusion in this volume. The papers cover a wide range of topics from work on formal aspects of normative and team based systems, to software engineering with organisational concepts, to applications of COIN based systems, and to philosophical issues surrounding socio-technical systems. They highlight not only the richness of existing work in the field, but also point out the challenges and exciting research that remains to be done in the area.

This book constitutes the thoroughly refereed post-conference proceedings of the 10th International Workshops on Coordination, Organizations, Institutions and Norms in Agent Systems, COIN 2014. The workshops were co-located with AAMAS 2014, held in Paris, France, in May 2014, and with PRICAI 2014, held in Gold Coast, QLD, Australia, in December 2014.

The 16 full papers were carefully reviewed and selected for inclusion in this volume. The papers cover a wide range of topics from work on formal aspects of normative and team based systems, to software engineering with organisational concepts, to applications of COIN based systems, and to philosophical issues surrounding socio-technical systems. They highlight not only the richness of existing work in the field, but also point out the challenges and exciting research that remains to be done in the area.

This book presents TDF (Tactics Development Framework), a practical methodology for eliciting and engineering models of expert decision-making in dynamic domains. The authors apply the BDI (Beliefs, Desires, Intentions) paradigm to the elicitation and modelling of dynamic decision making expertise, including team behaviour, and map it to a diagrammatic representation that is intuitive to domain experts.The book will be of value to researchers and practitioners engaged in dynamic decision making.

The earliest work on agents may be traced at least to the ?rst conceptualization of the actor model by Carl Hewitt. In a paper in an AI conference in the early 1970s, Hewitt described actors as entities with knowledge and goals. Research on actors continued to focus on AI with the development of the Sprites model in which a monotonically growing knowledge base could be accessed by actors (inspired by what Hewitt called “the Scienti?c Computing Metaphor”). In the late1970sandwellinto 1980s,controversyragedinAIbetweenthosearguingfor declarative languages and those arguing for procedural ones. Actor researchers stood on the side of a procedural view of knowledge, arguing for an open s- tems perspective rather than the closed world hypothesis necessary for a logical, declarativeview. In the open systemsview,agentshad armslength relationships and could not be expected to store consistent facts, nor could the information in a system be considered complete (the “negation as failure” model). Subsequent work on actors, including my own, focused on using actors for general purpose concurrent and distributed programming. In the late 1980s, a number of actor languages and frameworks were built. These included Act++ (in C++) by Dennis Kafura and Actalk (in Smalltalk) by Jean-Pierre Briot. In recent times, the use of the Actor model, in various guises, has proliferated as new parallel and distributed computing platforms and applications have become common:clusters,Webservices,P2Pnetworks,clientprogrammingonmulticore processors, and cloud computing.