A recent trend in programming language research is to use behavioral type theory to ensure various correctness properties of large-scale, communication-intensive systems. Behavioral types encompass concepts such as interfaces, communication protocols, contracts, and choreography. The successful application of behavioral types requires a solid understanding of several practical aspects, from their representation in a concrete programming language, to their integration with other programming constructs such as methods and functions, to design and monitoring methodologies that take behaviors into account. This survey provides an overview of the state of the art of these aspects, which we summarize as the pragmatics of behavioral types.

Precisely when the success of artificial intelligence (AI) sub-symbolic techniques makes them be identified with the whole AI by many non-computer-scientists and non-technical media, symbolic approaches are getting more and more attention as those that could make AI amenable to human understanding. Given the recurring cycles in the AI history, we expect that a revamp of technologies often tagged as “classical AI”—in particular,logic-basedones—will take place in the next few years. On the other hand, agents andmulti-agent systems(MAS) have been at the core of the design of intelligent systems since their very beginning, and their long-term connection withlogic-based technologies, which characterised their early days, might open new ways to engineerexplainable intelligent systems. This is why understanding the current status oflogic-based technologies for MASis nowadays of paramount importance. Accordingly, this paper aims at providing a comprehensive view of those technologies by making them the subject of asystematic literature review(SLR). The resulting technologies are discussed and evaluated from two different perspectives: the MAS and the logic-based ones.

A computational system is called autonomous if it is able to make its own decisions, or take its own actions, without human supervision or control. The capability and spread of such systems have reached the point where they are beginning to touch much of everyday life. However, regulators grapple with how to deal with autonomous systems, for example how could we certify an Unmanned Aerial System for autonomous use in civilian airspace? We here analyse what is needed in order to provide verified reliable behaviour of an autonomous system, analyse what can be done as the state-of-the-art in automated verification, and propose a roadmap towards developing regulatory guidelines, including articulating challenges to researchers, to engineers, and to regulators. Case studies in seven distinct domains illustrate the article.

With the invention and rapid improvement of data-capturing devices, such as satellite imagery and digital cameras, the information that archaeologists must manage in their everyday’s activities has rapidly grown in complexity and amount. In this work we present Indiana Finder, an interactive visualization system that supports archaeologists in the examination of large repositories of documents and drawings. In particular, the system provides visual analytic support for investigative analysis such as the interpretation of new archaeological findings, the detection of interpretation anomalies, and the discovery of new insights. We illustrate the potential of Indiana Finder in the context of the digital protection and conservation of rock art natural and cultural heritage sites. In this domain, Indiana Finder provides an integrated environment that archaeologists can exploit to investigate, discover, and learn from textual documents, pictures, and drawings related to rock carvings. This goal is accomplished through novel visualization methods including visual similarity ring charts that may help archaeologists in the hard task of dating a symbol in a rock engraving based on its shape and on the surrounding symbols

Automating a factory where robots are involved is neither trivial nor cheap. Engineering the factory automation process in such a way that return of interest is maximized and risk for workers and equipment is minimized is hence, of paramount importance. Simulation can be a game changer in this scenario but requires advanced programming skills that domain experts and industrial designers might not have. In this paper, we present the preliminary design and implementation of a general-purpose framework for creating and exploiting Virtual Environments via Natural language Agents (VEsNA). VEsNA takes advantage of agent-based technologies and natural language processing to enhance the design of virtual environments. The natural language input provided to VEsNA is understood by a chatbot and passed to an intelligent cognitive agent that implements the logic behind displacing objects in the virtual environment. In the complete VEsNA vision, for which this paper provides the building blocks, the intelligent agent will be able to reason on this displacement and on its compliance with legal and normative constraints. It will also be able to implement what-if analysis and case-based reasoning. Objects populating the virtual environment will include active objects and will populate a dynamic simulation whose outcomes will be interpreted by the cognitive agent; further autonomous agents, representing workers in the factory, will be added to make the virtual environment even more realistic; explanations and suggestions will be passed back to the user by the chatbot.