INTELLIGENT-PERSONAL-AGENT INTERFACE FOR OPERATING-SYSTEMS

A self-teaching intelligent-personal-agent interface (IPAI) for the VA X/VMS operating system has been designed and tested Its performance is based on (1) a priori knowledge about the operating system in use, an d about the specific user environment, and (2) learning by observing a user interact with the computer system. The interface combines a synt ax-based approach, a memory-based approach, and an approach based on i ntelligent personal agents. The implemented system was tested by users who completed evaluation forms. The best and worst properties of the implemented system are highlighted. Experiments show that the memory-b ased intelligent-agent approach enables designing very flexible and ad aptable systems that learn from past events without burdening the user . Memorized events enable good performance even in situations that wer e not anticipated by the designers. The classical rule based approach achieves similar performance for expected tasks, yet is less adaptable to changes in environment and demands more programming efforts. The i ntelligent-personal agents approach has been shown to be a promising d irection with the expected trust and competence problems. For mundane, easy tasks, the intelligent-personal-agents approach is very close to application maturity, thus enabling a step-up in man-machine communic ation.