|
Title:
|
ONTOLOGY-BASED HUMAN-MACHINE COLLECTIVE
INTELLIGENCE ENVIRONMENT FOR DECISION
SUPPORT |
|
Author(s):
|
Alexander Smirnov and Andrew Ponomarev |
|
ISBN:
|
978-989-8704-23-8 |
|
Editors:
|
Pedro Isaías |
|
Year:
|
2020 |
|
Edition:
|
Single |
|
Keywords:
|
Human-Machine Systems, Human-In-The-Loop, Collective Intelligence, Collaboration, Decision Support |
|
Type:
|
Full |
|
First Page:
|
107 |
|
Last Page:
|
114 |
|
Language:
|
English |
|
Cover:
|
|
|
Full Contents:
|
click to dowload 
|
|
Paper 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. |
|
|
|
|
|
|
