A new computer language for manufacturing is being used to link complex systems of equipment whose components are supplied by multiple vendors. The Cell Management Language (CML) combines computational tools from rule-based data systems, object-oriented languages, and new tools that facilitate language processing. These language tools, combined with rule processing, make it convenient to build new interpreters for interfacing and understanding a range of computer and natural languages ; hence, CML is being used primarily to define other languages in an interpretive environment, that is, as a meta-interpreter. For example, in CML it is quite easy to build an interpreter for machine tool languages that can understand and generate new part programs. Once interpreters for different machine and human languages have been constructed, they can be linked together into a system of interpreters. These interpreters can be used to make intelligent decisions for systemwide action planning and diagnostic error recovery. CML is being used in the factory environment to make turbine blade performs and has proven to greatly simplify the task of building complex control systems.

The objectives of this document (a part of a retrospective monograph on the AGE Project currently in preparation) are (1) to define what is meant by blackboard systems and (2) to show the richness and diversity of blackboard system designs. In Part 1 we discussed the underlying concept behind all blackboard systems -- the blackboard model of problem solving. We also traced the history of ideas and designs of some application systems that helped shape the blackboard model. In application systems, the blackboard system components are integrated into the domain knowledge required to solve the problem at hand.

Hillis's book, like its bibliography, has something to offer nearly everyone in the computer science community, even those with no background in computer architecture. The book provides a glimpse of what the next generation of computers will be like.

This report describes recent and continuing research in artificial intelligence and related fields being conducted at the University of Pennsylvania. Although AI research takes place primarily in the Department of Computer and Information Science ( in School of Engineering and Applied Science), many aspects of this research are preformed in collaboration with other engineering departments as well as other schools at the University, such as the College of Arts and Sciences, the School of Medicine, and Wharton School.

This article contains reports from the various research groups in the SUNY Buffalo Department of Computer Science, Vision Group, and Graduate group in Cognitive Science. It is organized by the different research topics. However, it should be noted that the individual projects might also be organized around the methodologies and tools used in the research, and, of course, many of the projects fall under more than one category.

The Advanced Computational Methods Center (ACMC) established at the University of Georgia in 1984, supports several research projects in artificial intelligence. The primary goal of AI research at ACMC is the design and installation of a logic-programming environment with advanced natural language processing and knowledge-acquisition capabilities on the university's highly parallel CYBERPLUS system from Control Data Corporation.

This article presents a summary of past and current artificial intelligence research within the Computer Science Department at East Texas State University (ETSU). The Computer Science Department at ETSU offers a master of science degree with an emphasis in artificial intelligence. AI research, both past and present, has been funded by a grant from E-Systems, Greenville Division. Other computing facilities available for artificial intelligence research are four workstations, each providing up to 20 users with LISP and PROLOG interpreters.

The Center for Automation and Intelligent Systems monocrystal turbine blades for jet engines that are made Research at Case Western Reserve University, founded by investment casting. Essentially, the part is made by in 1984, provides the setting and the administrative and pouring liquid metal into a ceramic mold, but the environment funding mechanisms for coordinating and focusing the capabilities in which this is done must be tightly controlled. of faculty members and students from many There are several other subprocesses that are also tightly disciplines and departments to deal with significant realworld controlled, such as making the mold. The total process is too complex for a single expert The center serves as an interface between separate system; rather, several different expert systems are needed basic research efforts in the various disciplines and academic and should be coordinated in some way, perhaps by a more departments and the multidisciplinary group efforts global expert system. Currently, we are constructing an needed to deal effectively with nontrivial real problems. Wax patterns appear to be essential for the factory of the future.

The major limitations in building large software have always been (a) its brittleness when confronted by problems that were not foreseen by its builders, and (by the amount of manpower required. The recent history of expert systems, for example highlights how constricting the brittleness and knowledge acquisition bottlenecks are. Moreover, standard software methodology (e.g., working from a detailed "spec") has proven of little use in AI, a field which by definition tackles ill- structured problems. But decades of work on such systems have convinced us that each of these approaches has difficulty "scaling up" for want a substantial base of real world knowledge.

Further, new application domains such as computer -aided design (CAD), computer- aided manufacturing (CAM), and image understanding based on formal logic require novel concepts in knowledge representation and inference beyond the capabilities of current production rule systems. Fundamental research in artificial intelligence is concentrated at Corporate Research and Development (CR&D), with advanced development and applications pursued in parallel efforts by operating departments. The fundamental research and advanced applications activities are strongly coupled, providing research teams with opportunities for field evaluations of new concepts and systems. This article summarizes current research projects at CR&D and gives an overview of applications within the company.