Acquisition and support of goal-based tasks

Abstract To make plan-based expert systems more accessible to end users and to support user tasks effectively, we present a system that makes the functionality of AI-planning techniques seem natural and immediately understandable. In particular, we present a task support system with a graphical interaction language for the acquisition and display of plan knowledge, where the intended users are domain experts and novices and where previous computer literacy is not required. Based on existing theories in cognitive science and on our own experimental research, we propose a cognitive model of the users' view of tasks. The model postulates the domain experts' ability to recall relevant parts of self-performed tasks in the application domain. The validity of the model is demonstrated in a paper-and-pencil experiment. Employing a cognitive systems engineering approach, we use the cognitive model, a stage process model of knowledge acquisition, and requirements from the plan formalism to specify DACRON, a system for plan acquisition and task support. DACRON supports the acquisition of plan knowledge by providing graphical representations of domain entities from the users' point of view. DACRON checks the consistency of specified units and graphically aids the debugging process. DACRON also allows the animated presentation of the planning process and its results. To evaluate the usability of DACRON and the relevance of the acquired and displayed knowledge in application domains, experimental studies involving 39 users were conducted. The studies show that over 90% of the subjects could easily use DACRON to enter knowledge, and 80% of the entered knowledge was relevant and correct. In the case of knowledge display, subjects were able to use the displayed knowledge effortlessly and apply it to solve 95% of the domain problems presented.