In Al knowledge representation schemes, structures that describe other structure:: are said to represent "meta-knowledge." Knowledge about other knowledge can be either about the form of the representation scheme itself (e.g., its syntax) or about the "facts" that are represented (their origin, reliability, Importance, etc.). After reviewing the use of explicit meta-knowledge In several systems, some studies of human behavior that Indicate people's ability to reason about what they know and about how they reason are described. The concept of meta-level knowledge captures intrinsic, commonplace properties of human cognition that are central to an understanding of memory and Intelligence. The use of meta-knowledge In Al systems like MYCIN, which have reached humanexpert-level performance In complex domains, Is a key breakthrough In the design of "knowledge-based" Intelligent systems. Meta-level knowledge has been used in these systems primarily in the implementation of "introspective" processes: Acquisition of new knowledge and explanation of the system's reasoning to users. The usefulness of meta-level descriptions for these and other functions has prompted proposals for their incorporation in several new general-purpose representation schemes, like KRL, as described In the next section.

As the patient setting changes--e.g., as a patient starts Lo breathe on his own during removal (weaning) from the ventilator--the same measurement values lead to different interpretations. In order to properly interpret data collected during changing therapeutic contexts, the knowledge base includes a model of the stages that a patient follows from admission to the unit through the end of the critical monitoring phase. Recognition of the appropriate patient context is an essential step in determining the meaning of most physiological measurements. The program maintains a description of the current and optimal ventilatory therapies for any given time. The list of states and possible state transitions are represented in Figure 1.

The Intent of the protocol is to show AGE from the user's point of view. The main body describes the motivations for and the description of the facilities in AGE.

AGE is a system designed to aid knowledge engineers build knowledge-based programs. We have built a laboratory of building blocks which the user can assemble in various ways to fit a particular problem. This paper describes the facilities available to the user and descibes an example program built with AGE.

It has been noted that the clinical computer programs The more "human-like" the consultation system, the most acceptable to physicians are those which more likely that the busy physician will see it as a perform tasks that the physician himself is either viable alternative to interaction with a human consultant.

A. Conduct of Science: Computers and Communications and opportunities for the scientific community to share The claim of science to universal validity is supportable only

A clinical investigator graphical capabilities which can plot specific parameters for a keeping the records of his study patients on such a system can patient over time 1126]. However, it is in the analysis of stored use the program's statistical capabilities for data analysis.

A program for selecting antibiotic therapy is described that makes sophisticated recommendations and provides simple, useful explanations of its reasoning for a user. Our method is to structure the therapy optimization problem in terms of local and global solution criteria that are applied in a generate-and-test algorithm. Generation of therapy recommendations is directed by a fixed, ordered set of canonical instructions that describe the global characteristics of a recommendation. Other factors are dealt with in a "planning" phase particular to each organism for which therapy is to be prescribed, and the test phase that incorporates patient considerations such as allergies and age. We demonstrate the advantages of this canonical form for explanation, comparison of alternative recommendations, and a simple instructive capability.

These knowledge bases are generally built by interviewing human experts to extract the knowledge they use to solve problems in their area of expertise. However, it is not clear that the organization and level of abstraction of this performance knowledge is suitable for use in a tutorial program. We are exploring this problem in the GUIDON tutorial program, using the knowledge bases of MYCIN-like expert systems. MYCIN is a knowledge-based program that provides consultations about infectious disease diagnosis and therapy (Shortliffe, 1974). In MN CIN, domain relations and facts take the form of rules about what to do in a given circumstance. A principle feature of this formalism is the separation of the knowledge base from the interpreter for applying it. This makes the knowledge accessible for multiple uses, including application to particular problems (i.e. for "performance") and explanation of reasoning (Davis, 1976). We have most recently used the MYC1N knowledge base as the foundation of a tutorial system, called GUIDON.

We describe the development and (partial) Implementation of an "automated consultant" to advise non-expert engineers In the use of a general-purpose structural analysis program. The analysis program numerically simulates the behavior of a physical structure subjected to various mechanical loading conditions. The automated consultant, called SACON (Structural Analysis CONsultant), Is based on a version of the MYCIN program [Shortliffe74], originally developed to advise physicians In the diagnosis and treatment of infectious diseases. The domain-specific knowledge in MYCIN Is represented as situation-action rules, and is kept independent of the "inference engine" that uses the rules. By substituting structural engineering knowledge for the medical knowledge, the program was converted easily from the domain of Infectious diseases to the domain of structural analysis.