While some 30 years ago the addition of computers to the human-machine environment was considered only for routine tasks in support tasks in support of the human, the balance has dramatically shifted to the computer now being able to perform almost any task the human is willing to delegate. Advances in automation and especially Artificial Intelligence have enabled the formation of rather unique teams with human and (electronic) machine members. Such teams are still led by the human with the machine as a subordinate associate or assistant, but as these become more complex, the automation that the human has to interact with is becoming increasingly intelligent and capable. / This thesis proposes a conceptual framework for automation and human-machine teaming that is based on developments in military aviation under the headings of Pilot's Associate or Crew Assistant. The starting point is the introduction of the machine-assistant into the traditional situation where the human is solely responsible for all activities. Analogies from classical control theory will be used to identify the boundaries, interfaces and tasks to be shared between the human and machine-assistant. Several schemes for task classification and allocation aim to establish a complementary relationship which will allow the human to stay in command and to utilise assistance of the machine to its fullest potential. Task management and coordination are requirements emphasised by the introduction of automation. Their correct implementation is extremely important in dealing with abnormal and high-workload situations. / The framework will be placed in the context of Cognitive Systems Engineering and Human Centered Automation. Both disciplines have been developed to provide answers to the problems associated with the aggressive introduction of automation into the traditional human-machine environment. Both disciplines also arrive at similar approaches which refocus on the human as the most important element in this environment. Several concepts of cognitive engineering and cognitive automation provide a theoretical reference for the proposed framework. / The conceptual framework highlights that the machine-assistant interactions are complex and that these interactions should exhibit intelligent behaviour in order to remain transparent to the human-operator at all times. Artificial Intelligence and Advanced Information Processing are technologies which are expected to be able to handle this complexity, to support a sophisticated human-machine dialogue and to minimise the cognitive gap between human and machine. Intelligent Agents, and in particular agents that apply the Belief-Desire-Intention architecture, have become attractive options to implement machine-assistants. Several areas for further research, such as human-agent teaming architectures, human-agent coordination and agent learning will be discussed. / Thesis (PhDElectronicEngineering)--University of South Australia, 2003.
| Identifer | oai:union.ndltd.org:ADTP/290061 |
| Date | January 2003 |
| Creators | Urlings, Pierre |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
| Rights | copyright under review |
Page generated in 0.0013 seconds