This is the second part of a two-part article describing AI work at the NASA Johnson Space Center (JSC). In the Space Operations Directorate, these groups include (1) the Mission Planning and Analysis Division (MPAD) - Technology Development and Applications Branch, (2) the Spacecraft Software Division, and (3) the Systems Division - Systems Support Section. This second part of the article describes the AI work in the Space Operations Directorate. The first part of the article, published in the last week of AI Magazine, (7:1, Summer 1986) described the AI work in the Research and Engineering Directorate.

I review the research leading from the GUIDON rule-based tutoring system, including the reconfiguration of MYCIN into NEOMYCIN and NEOMYCIN's generalization in the heuristic classification shell, HERACLES. The presentation is organized chronologically around pictures and dialogues that represent conceptual turning points and crystallize the basic ideas. My purpose is to collect the important results in one place, so they can be easily grasped. In the conclusion, I make some observations about our research methodology.

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.

In this article, we present a programming language for expressing classificatory problem solvers. CSRL (Conceptual Structures Representation Language) provides structures for representing classification trees, for navigating within those trees, and for encoding uncertainly judgments about the presence of hypotheses. We discuss the motivations, theory, and assumptions that underlie CRSL. Also, some expert systems constructed with CSRL are briefly described.

This article provides some basic assistance to entrepreneurs involved in artificial intelligence, offering a synthesis of standard business-planning and capital-raising practices. Three main areas are discussed: (1) developing a corporate strategy, (2) developing a business plan that works, and (3) approaching sources of capital.

This is the second part of a two-part article describing AI work at the NASA Johnson Space Center (JSC). Research and applications work in AI is being conducted by several groups at JSC. These are primarily independent groups that interact with each other on an informal basis. In the Research and Engineering Directorate, these groups include (1) the Artificial Intelligence and Information Sciences Office, (2) the Simulation and Avionics Integration Division, (3) the Avionics Systems Division, and (4) the Tracking and Communications Division. In the Space Operations Directorate, these groups include (1) the Mission Planning and Analysis Division (MPAD) - Technology Development and Applications Branch, (2) the Spacecraft Software Division, and (3) the Systems Division - Systems Support Section. This second part of the article describes the AI work in the Space Operations Directorate. The first part of the article, published in the last week of AI Magazine, (7:1, Summer 1986) described the AI work in the Research and Engineering Directorate.

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.

The Portrait Programs Project grew out of hyperinterdisciplinarianism of the famed Gigabase Sculpture Group, in turn stimulated by recent cutbacks in government support for the arts. The National Endowment for the Humanities and the National Science Foundation had jointly funded the Gigabase Sculpture Project to foster the literary/musical genre of composing genetic codes for novel organisms. Later, artists trained in recombinant DNA technology designed massive Brancusi-esque statues of living cytoplasmic jelly. However, Art For Art's Sake objectives of these giblet sculptors were compromised by precautions necessary after discovery of the "Gogol's-Theorem Bomb" that threatened to get loose and jam all DNA replication in the biosphere; not even viruses would have survived.

I review the research leading from the GUIDON rule-based tutoring system, including the reconfiguration of MYCIN into NEOMYCIN and NEOMYCIN's generalization in the heuristic classification shell, HERACLES. The presentation is organized chronologically around pictures and dialogues that represent conceptual turning points and crystallize the basic ideas. My purpose is to collect the important results in one place, so they can be easily grasped. In the conclusion, I make some observations about our research methodology.