Intelligent Agents for Operator Training and Task Guidance
Intelligent software agents can help the operators of complex industrial equipment both with training and in the performance of their tasks. During training, the operators practice their tasks in a simulated environment. The intelligent agent guides operators through the steps of complex procedures, giving positive and negative feedback on their actions, and adapting to their skill level. We have developed generic software for building such software agents and have demonstrated it by building an agent for training operators of a simulated gas turbine engine.
Background & Objective: This work extends the COLLAGEN middleware for building collaborative agents. Our goals are to enhance existing training systems by adding more sophisticated tutorial strategies and also to build new training and task guidance systems. Potential application areas include supervisory control and data acquisition (SCADA) systems, such as industrial plant control centers, equipment maintenance tasks, such as elevator repair, and the use of complex software interfaces, such as computer-aided design tools.
Technical Discussion: Our approach to operator training is based on "learning by doing." The software agent guides the operator through a sequence of example scenarios that incrementally expose the operator to the full complexity of the task to be learned. During the training process, the agent maintains a model of the operator's proficiency in each part of the task, so it can appropriately introduce new subtasks as well as give the operator the opportunity to practice previously taught knowledge. Using COLLAGEN as our implementation base gives the training system developer two major advantages. First, we have an application-independent architecture in which pedagogical strategies are encoded in an application-independent manner; this allows the developer to reuse a large amount of code when creating a new training agent. Second, the same task model created to support a training agent can be reused to produce an agent which will act as an advisor or intelligent assistant to an operator during the actual performance of his job, if desired.
Outside Collaborations: We are collaborating with the University of Southern California, Information Sciences Institute and the MITRE Corporation on embedded training applications in general.
Contact: Richard (Dick) Waters
| Technical Reports: | |
| A Plug-in Architecture for Generating Collaborative Agent Responses | |
| Using a Model of Collaborative Dialogue to Teach Procedural Tasks | |
| Incorporating Tutorial Strategies into an Intelligent Assistant | |
Technology Areas:
Off the Desktop Interaction and Display
Artificial Intelligence
Spoken Language Interfaces
Modification Date: September 12, 2007
