AI Communications track on agreement technologies

Abstract

The area of agreement technologies is receiving increased attention within the Artificial Intelligence research community. This is because current intelligent software applications are often based on components that are autonomous, capable of sophisticated ways of interacting, massively distributed, and quite often embedded in all sorts of appliances and sensors. These autonomous components, usually termed agents, need to be socially-aware in order to successfully achieve their goals. The important research question is how can we build software systems as collections of these components and guarantee that they interoperate correctly, and are thus reliable, especially when the components are complex, with autonomic and adaptive features, and open? One of the basic assumptions in the development of agreement technologies is that the components are independently developed and thus no a priori assumptions on their workings can be made. Correct interoperability needs to be based on a two step process: first, the establishment of explicit agreements among the entities and then the execution of those agreements. The generation of agreements requires techniques that cover the two fundamental aspects of potential disagreement: semantics and co-ordinated action, for instance, semantic alignment techniques to allow compo-