ONTOLOGY-BASED HUMAN-MACHINE COLLECTIVE INTELLIGENCE ENVIRONMENT FOR DECISION SUPPORT

Abstract

The paper proposes the design of a computer environment aiming at the support of human-machine collective intelligence in decision-making problems. The environment supports two main processes taking place during the collective effort on a complex problem: process organization (planning the activities and the distribution of the responsibilities) and building a solution (plan implementation). To address the problem of human-machine interoperability, the environment leverages multi-aspect ontologies, allowing to represent the status of the process and information about the problem in a human- and machine-readable way. The proposed solution can be employed in building interoperable human-machine collaborative systems in variety of complex problem domains.