Multi-Agent Based System for Analysing Stress using the StressCafé
Ghosh Anusua, Tweedale Jeffery W., Nafalski Andrew, Maureen Frances Dollard · Frontiers in artificial intelligence and applications · 2012
Work related stress affects people from all professions and is a growing concern because it is reported as a common cause of occupational illness. Work stress can be prevented if it is identified; measured and appropriate changes are made to the work environment. Intelligent agent technology to solve both simple and complex problems has been used in many applications but this technology has not been applied in psychology. These agents provide better management of complex systems or processes as the level of abstraction is much higher and the programming problems focus on specifying an agent’s behaviour and communication with other agents. In this paper, we present a novel approach of using Multi-Agent System (MAS) to effectively maintain, analyse and update work-stress related data. The MAS part of Intelligent Multi-Agent Decision Analyser (IMADA) has been integrated with the existing Intelligent Agent Framework (IAF) model that has been developed in conjunction with the StressCafé using the Australian Workplace Barometer (AWB) tool. The intelligent decision analyser Decision Analyser (DA) will be developed using a hybridized algorithm that uses neural network and fuzzy logic.