A conception of collaborative decision support systems: approach and platform architecture

The paper describes a general conception of collaborative decision support systems, in which teams providing decision support a) are formed flexibly in accordance with the problem and b) consist of both human experts and intelligent agents implementing AI methods and techniques. An analysis of the key problems of creating collaborative decision support systems based on the collaboration of humans and AI is carried out, the following problems are highlighted: ensuring interoperability (mutual understanding) between heterogeneous team members, reconciling differing positions of participants, ensuring trust between participants, ensuring the effectiveness of joint actions planning and maintaining a balance between predefined workflows and self-organization. Principles for constructing such systems have been formed, offering solutions to the identified problems. In particular, it is proposed to employ an ontology-oriented representation of information about the problem (in the form of multi-aspect ontology), a set of methods for monitoring team activities, reputation scheme, elements of explainable AI, as well as mechanisms of limited self-organization. The proposed concept forms the basis of a software platform for the development of collaborative decision support systems, the main architectural provisions of which are also presented in the paper. The use of the platform is illustrated by an example from the field of rational management of road infrastructure and the creation of a collaborative DSS for the development of measures to reduce road accidents.