Multi-agent systems research in the United Kingdom

Abstract

Multi-agent systems have been a core research topic in artificial intelligence for several decades. A multiagent system consists of multiple decision-making agents -which may be software-based AI systems, physicallyembodied robots, or humans -which must interact in a shared environment in pursuit of their goals. Multi-agent systems research spans a range of technical problems, such as how to design planning and learning algorithms which enable agents to achieve their goals; how to design multi-agent systems to incentivise certain behaviours in agents; how information is communicated and propagated among agents; and how norms, conventions, and roles may emerge in multi-agent systems. A vast array of applications have been addressed using multi-agent methodologies, including autonomous driving, multi-robot factories, automated trading, commercial games, automated tutoring, and robotic rescue teams.The purpose of this special issue is to showcase current multi-agent systems research led by university and industry groups based in the United Kingdom. Research groups and institutes in the UK which have significant activity in multi-agent systems research were invited to submit an article describing: (1) the technical problems in multi-agent systems tackled by the group (their core research agenda), including applications and industry collaboration; (2) the main approaches developed by the group and any key results achieved; and (3) important open challenges in multi-agent systems research from the perspective of the group.A large number of high-quality submissions were received, of which 14 were included for publication in the special issue. These articles represent a broad set of research topics within the field of multi-agent systems, showcasing the strength of contributions made by UK-based research groups in both universities and industry. We believe the open research problems discussed in each of the articles will provide a rich resource for researchers in this field, both new and old.Research groups from the following organisations are represented in the special issue (ordered alphabetically

A Fine Wool and Cashmere Identification System Incorporating Decision Tree Algorithms

“…The simulation experiment was carried out under the simulation environment of Matlab7.0, and the processing scheme suitable for the fiber image was determined. Finally, according to the preprocessed image, the automatic measurement of cashmere diameter was realized by using the subsection measurement algorithm [4]. The experimental results show that the measurement method adopted in this paper improves the measurement accuracy of cashmere diameter to a certain extent.…”