Resilience, reliability, and coordination in autonomous multi-agent systems

Acknowledgements The research reported in this paper was funded and supported by various grants over the years: Robotics and AI in Nuclear (RAIN) Hub (EP/R026084/1); Future AI and Robotics for Space (FAIR-SPACE) Hub (EP/R026092/1); Offshore Robotics for Certification of Assets (ORCA) Hub (EP/R026173/1); the Royal Academy of Engineering under the Chair in Emerging Technologies scheme; Trustworthy Autonomous Systems “Verifiability Node” (EP/V026801); Scrutable Autonomous Systems (EP/J012084/1); Supporting Security Policy with Effective Digital Intervention (EP/P011829/1); The International Technology Alliance in Network and Information Sciences.Peer reviewedPostprin

Engineering Reliable Multiagent Systems (Dagstuhl Seminar 19112)

This report documents the program and outcomes of Dagstuhl Seminar 19112 "Engineering Reliable Multiagent Systems". The aim of this seminar was to bring together researchers from various scientific disciplines, such as software engineering of autonomous systems, software verification, and relevant subareas of AI, such as ethics and machine learning, to discuss the emerging topic of the reliability of (multi-)agent systems and autonomous systems in particular. The ultimate aim of the seminar was to establish a new research agenda for engineering reliable autonomous systems

Towards intelligent transport systems: geospatial ontological framework and agent simulation

In an Intelligent Transport System (ITS) environment, the communication component is of high significance as it supports interactions between vehicles and the roadside infrastructure. Existing studies focus on the physical capability and capacity of the communication technologies, but the equally important development of suitable and efficient semantic content for transmission has received notably less attention. Using an ontology is one promising approach for context modelling in ubiquitous computing environments. In the transport domain, an ontology can be used both for context modelling and semantic contents for vehicular communications. This research explores the development of an ontological framework implementing a geosemantic messaging model to support vehicle-to-vehicle communications. To develop an ontology model, two scenarios (an ambulance situation and a breakdown on the motorway) are constructed to describe specific situations using short-range communication in an ITS environment. In the scenarios, spatiotemporal relations and semantic relations among vehicles and road facilities are extracted and defined as classes, objects, and properties/relations in the ontology model. For the ontology model, some functions and query templates are also developed to update vehicles’ movements and to provide some logical procedures that vehicles need to follow in emergency situations. To measure the effects of the vehicular communication based on the ontology model, an agent-based approach is adopted to dynamically simulate the moving vehicles and their communications following the scenarios. The simulation results demonstrate that the ontology model can support vehicular communications to update each vehicle’s context model and assist its decision-making process to resolve the emergency situations. The results also show the effect of vehicular communications on the efficiency trends of traffic in emergency situations, where some vehicles have a communication device, and others do not. The efficiency trends, based on the percentage of vehicles having a communication device, can be useful to set a transition period plan for implanting communication devices onto vehicles and the infrastructure. The geospatial ontological framework and agent simulation may contribute to increase the intelligence of ITS by supporting data-level and application-level implementation of autonomous vehicle agents to share knowledge in local contexts. This work can be easily extended to support more complex interactions amongst vehicles and the infrastructure