We argue that the time between mission conception and implementation can be radically reduced, that launch mass can be slashed, that totally autonomous robots can be more reliable than ground controlled robots, and that large numbers of robots can change the tradeoff between reliability of individual components and overall mission success. Lastly, we suggest that within a few years it will be possible at modest cost to invade a planet with millions of tiny robotsJournal of The British Interplanetary Society, Vol. 42, pp 478-485

AAAI is a society devoted to supporting the progress in science, technology and applications of AI. I thought I would use this occasion to share with you some of my thoughts on the recent advances in AI, the insights and theoretical foundations that have emerged out of the past thirty years of stable, sustained, systematic explorations in our field, and the grand challenges motivating the research in our field.

The goal of intelligent computer-aided engineering (ICAE) is to construct computer programs that capture a significant fraction of an engineer's knowledge. Today, ICAE systems are a goal, not a reality. This article attempts to refine that goal and suggest how to get there. We begin by examining several scenarios of what ICAE systems could be like. Next we describe why ICAE won't evolve directly from current applications of expert system technology to engineering problems. I focus on qualitative physics as a critical area where progress is needed, both in terms of representations and styles of reasoning.

Real-time domains present a new and challenging environment for the application of knowledge-based problem-solving techniques. However, a substantial amount of research is still needed to solve many difficult problems before real-time expert systems can enhance current monitoring and control systems. In this article, we examine how the real-time problem domain is significantly different from those domains which have traditionally been solved by expert systems. We conduct a survey on the current state of the art in applying knowledge-based systems to real-time problems and describe the key issues that are pertinent in a real-time domain. The survey is divided into three areas: applications, tools, and theoretic issues. From the results of the survey, we identify a set of real-time research issues that have yet to be solved and point out limitations of current tools for real-time problems. Finally, we propose a set of requirements that a real-time knowledge-based system must satisfy.

Sargur N. Srihari is a professor and acting chairman of the Department of Computer Science, State University of New York (SUNY) at Buffalo. The author of "Recognizing Address Blocks on Mail Pieces," Srihari is an associate editor of the journal Pattern Recognition and is chairman of the technical committee on text-processing applications of the International Mike Baird, who coauthored the tribute to Kvetoslav Prazdny, is manager of Association for Pattern Recognition. Srihari is also currently directing two Intelligence Center 1185 Coleman Avenue, Santa Clara, California 95052. Jeffrey Stone is a consultant who watches the computer industry and Jonathan J. Hull is a research assistant Digital Equipment Corporation that reports new developments and trends. The opinions expressed "Recognizing Address Blocks on Mail address is Knowledge Systems Corporation, in his article are his own. Jeffrey Stout is on the research staff of computer vision, and artificial intelligence. An Expert Elevator report on AI and education, is an Buffalo, where he is also currently Designer that Uses Knowledge-Based associate professor in the Department working on his Ph.D. His research Backtracking." of Mathematics and Computer Science interests include image processing, at Millersville University, computer graphics, and computer segmentation Jay M. Tenenbaum, who coauthored Millersville, Pennsylvania 1755 1. Palumbo is a the tribute to Kvetoslav Prazdny, is a coauthor of "Recognizing Address Schlumberger Fellow at the Schlumberger John McDermott is a principal scientist Blocks on Mail Pieces."

The Oak Ridge National Laboratory (ORNL) Center for Engineering Systems Advanced Research (CESAR) is a national center for multidisciplinary long-range research and development (R&D) in machine intelligence and advanced control theory. Intelligent machines (including sensor-based robots) can be viewed as artificially created operational systems capable of autonomous decision making and action. One goal of the research is autonomous remote operations in hazardous environments. This review describes highlights of CESAR research through 1986 and alludes to future plans.

In 1940, a 20-year-old science fiction fan from Brooklyn found that he was growing tired of stories that endlessly repeated the myths of Frankenstein and Faust: Robots were created and destroyed their creator; robots were created and destroyed their creator; robots were created and destroyed their creator-ad nauseum. So he began writing robot stories of his own. "[They were] robot stories of a new variety," he recalls. "Never, never was one of my robots to turn stupidly on his creator for no purpose but to demonstrate, for one more weary time, the crime and punishment of Faust. My robots were machines designed by engineers, not pseudo-men created by blasphemers. My robots reacted along the rational lines that existed in their'brains' from the moment of construction. " In particular, he imagined that each robot's artificial brain would be imprinted with three engineering safeguards, three Laws of Robotics: 1. A robot may not injure a human being or, through inaction, allow a human being to come to harm. 2. A robot must obey the orders given it by human beings except where such orders would conflict with the first law. The young writer's name, of course, was Isaac Asimov (1964), and the robot stories he began writing that year have become classics of science fiction, the standards by which others are judged. Indeed, because of Asimov one almost never reads about robots turning mindlessly on their masters anymore. But the legends of Frankenstein and Faust are subtle ones, and as the world knows too well, engineering rationality is not always the same thing as wisdom. M Mitchell Waldrop is a reporter for Science Magazine, 1333 H Street N.W., Washington D C. 2COO5. Reprinted by permission of the publisher.

The development of an online turbine generator diagnostic system is described from conception to initial field verification. The system is composed of a data center located in the power plant that collects data from online measurement devices and communicates these data to a centralized diagnostic facility in Orlando, Florida, where the actual diagnosis is done. The resulting diagnosis and recommended actions are transmitted to the power plant where they are displayed to the operator by the data center. The market-place need, initial approaches to the product, system field verification are described.

The development of an online turbine generator diagnostic system is described from conception to initial field verification. The system is composed of a data center located in the power plant that collects data from online measurement devices and communicates these data to a centralized diagnostic facility in Orlando, Florida, where the actual diagnosis is done. The resulting diagnosis and recommended actions are transmitted to the power plant where they are displayed to the operator by the data center. The market-place need, initial approaches to the product, system field verification are described. The artificial intelligence (AI) diagnostic program has been diagnosing seven large utility generators since July 1984 and has correctly diagnosed a significant number of generator and instrumentation problems. Issues such as a centralized approach, rule base quality control, and the range of resources needed for a successful product are discussed.

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.