Approaches to knowledge acquisition : the Instructable Production System Project

Progress in building systems that acquire knowledge from a variety of sources depends on determining certain functional requirements and ways for them to be met. Experiments have been performed with learning systems having a variety of functional components. The results of these experiments have brought to light deficiencies of various sorts, in systems with various degrees of effectiveness. The components considered here are: interaction language; organization of procedural elements; explanation of system behavior; accommodation to new knowledge; connection of goals with system capabilities; reformulation (mapping) of knowledge; evaluation of behavior; and compilation to achieve efficiency and automaticity. A number of approaches to knowledge acquisition tried within the Instructable Production System (IPS) Project are sketched.* 1. The lnst ructable Production System Project The IPS project [6] attempts to build a knowledge acquisition system tinder a number of constraints. The instructor of the system gains all information about IPS by observing its interactions with its environment (including the instructor). Interaction is to take place in (restricted) natural language. The interaction is mixed initiative, with both participants free to try to influence the direction. Instruction may be about any topic or phenomenon in the system’s external or internal environment. Knowledge accumulates over the lifetime of the system. *This research was sponsored by the Defense Advanced Research Projects Agency (DOD), ARPA Order No. 3597, monitored by the Air Force Avionics Laboratory Under Contract F33615-78-C-1551. The views and conclusions contained in this document ate those of the author and should not be interpreted as representing the official polictes, either expressed or implied, of the. Defense Advanced Research Projects Agency or the US Government. Throughout these IPS experiments, the underlying knowledge organization has been Production Systems (PSs) [2], a form of rule-based system in which learning is formulated as the addition to, and modification of, an unstructured collection of production rules. Behavior is obtained through a simple recognize-act cycle with a sophisticated set of principles for resolving conflicts among rules. The dynamic short-term memory of the system is the Working Memory (WM), whose contents are matched each cycle to the conditions of rules in the long-term memory, Production Memory. Study of seven major attempts to construct instructable PSs with various orientations leads to recognizing the centrality of eight functional components. Listing the components and their embodiment in various versions of IPS can contribute to research on learning systems in general, by clarifying some of the important subproblems. This discussion is the first overview of the work of the project to date, and indicates its evolutionary development. Members of the IPS project are no longer working together intensively to build an instructable F ‘S, but individual studies that will add to our knowledge about one or more of these components are continuing. Progress on the problem of efficiency of PSs has been important to the IPS project [3], but will not be discussed further here. 2. Essential Functional Components of Inst ructable Systems The components listed in this section are to be interpreted loosely as dimensions along which learning systems might vary. Interaction The content and form of communications -A between instructor and IPS can have a lot to do with ease and effectiveness of instruction. In particular, it is important to know how closely communications correspond to internal IPS structures. Similarly, we must ask how well the manifest behavior of IPS indicates its progress on a task. An IPS can have various orientations towards interactions, ranging from passive to active, with maintenance of consistency and assimilation into existing structures. Organization. Each version of IPS approaches the issue of obtaining coherent behavior by adopting some form of organization of its ‘procedural’ knowledge. This may involve such techniques as collecting sets of rules into ‘methods’ and using signal conventions for sequencing. Whether IPS can explain its