Intelligence (AAAI) hopes that these This year's conference featured a new A talk united by a set of related research This year's program represented an by Jim Green0 addressed modeling issues. Constraint this approach is not seen There was time to interact Reasoning and Component Technologies as often today. Where is it session following each set of presentations. Highlights from the program focused on a presentation on among the accepted papers. A panel entitled "How Long which ran for two consecutive days Until the Household Robot: The For the first time, Innovative Applications during the conference. The emergence State of the Art in Robotics" featured in Artificial Intelligence (IAAI) of the forum Planning, Perception, speakers from industry and Carnegie presentations and AI Online interactive and Robotics reflected a recent trend Mellon's Robotic Institute, who panels were presented concurrently in Planning, with videotapes and a live robot providing an impressive demonstration Perception, and Robotics included demonstration.

This article argues that autonomy, not problem-solving prowess, is the key property that defines the intuitive notion of "intelligent creature." To build an intelligent artificial entity that will act autonomously, we must first understand the attributes of a system that lead us to call it autonomous. The presence of these attributes gives autonomous systems the appearance of nondeterminism, but they can all be present in deterministic artifacts and living systems. We argue that autonomy means having the right kinds of goals and the ability to select goals from an existing set, not necessarily creating new goals. We analyze the concept of goals in problem-solving systems in general and establish criteria for the types of goals that characterize autonomy.

A performance evaluation of 15 text-analysis systems was recently conducted to realistically assess the state of the art for detailed information extraction from unconstrained continuous text. Reports associated with terrorism were chosen as the target domain, and all systems were tested on a collection of previously unseen texts released by a government agency. Based on multiple strategies for computing each metric, the competing systems were evaluated for recall, precision, and overgeneration. The results support the claim that systems incorporating natural language-processing techniques are more effective than systems based on stochastic techniques alone. A wide range of language-processing strategies was employed by the top-scoring systems, indicating that many natural language-processing techniques provide a viable foundation for sophisticated text analysis. Further evaluation is needed to produce a more detailed assessment of the relative merits of specific technologies and establish true performance limits for automated information extraction.

Building new knowledge-based systems today usually entails constructing new knowledge bases from scratch. It could instead be done by assembling reusable components. System developers would then only need to worry about creating the specialized knowledge and reasoners new to the specific task of their system. This new system would interoperate with existing systems, using them to perform some of its reasoning. In this way, declarative knowledge, problem- solving techniques, and reasoning services could all be shared among systems. This approach would facilitate building bigger and better systems cheaply. The infrastructure to support such sharing and reuse would lead to greater ubiquity of these systems, potentially transforming the knowledge industry. This article presents a vision of the future in which knowledge-based system development and operation is facilitated by infrastructure and technology for knowledge sharing. It describes an initiative currently under way to develop these ideas and suggests steps that must be taken in the future to try to realize this vision.

First, the the other does. No theorist is going Thank you for the opportunity to split between the neats and scruffies to spend his or her time attempting respond to the letters by Jim Hendler, is old and institutionalized, as to bring precision to a mess of hacks, James Herbsleb and Mike Wellman Hendler points out. Few researchers kludges and "knowledge," and no regarding my survey of the Eighth are trained in both camps. Second, system builder is apt to find the National Conference on Artificial the pathologies that researchers in attempt informative. MAD does not Intelligence (AI Magazine, Volume 12, AAAI-90 themselves attributed to mean business as usual with occasional No. 1).

Machine, I raised (much more playfully) one of the questions David M. West and Larry E. Travis raise in their important article, "The Computational Metaphor and Artificial Intelligence". AI might CA) has added a download microcode FL) has developed an expert system have gone off on the wrong track, enhancement to its Hi-Track expert to set its prices nationwide for Alamo's rather like Columbus believing he'd system. The enhancement will allow rental cars. The embedded system analyzes discovered the Indies. Columbus Hi-Track to remotely identify and the competition's prices, compares hadn't discovered the Indies; in fact solve potential problems in a customer's them to Alamo's, and then he'd stumbled on something as least storage subsystem, over the telephone.

A memorial tribute to AI researcher Jonathan King who died of cancer in 1991.

Each node has between Joshi), and computational vision (S. Papers were presented by The Department of Electronics, Government under contract with Indian companies. Seven major research and KBCS applications, including expert logic programming (which teaching centers and a number of systems for government administration, seems to be well developed in India), associated institutions are involved expert systems for engineering and reasoning. The level of most presentations are the Center for the Development vision system applications, and was good and of an international of Advanced Computing (Pune), the KBCS applications in and for ancient flavor. The audience was Department of Electronics (New Indian sciences; and language-processing unusually active, initiating discussions Delhi), The Indian Institute of Science technologies, including natural and friendly controversies.

AI research is conducted at a number of academic and research units at the Georgia Institute of Technology. Some of this research is basic in nature, and some has an applied character to it. This article briefly describes basic AI research in the College of Computing at Georgia Tech.

This article picks up the call for a reflective examination of the prevailing computational metaphor of AI (and philosophical presuppositions behind it) by sketching alternatives that might serve as seeds for discussion-specifically, the seven alternatives introduced in our previous article (see "AI Magazine, spring 1991). The relative strengths and weaknesses of the alternatives are contrasted with those of the computational metaphor.