Bratman's definition of intention is papers range from philosophical This review is organized around the jumping-off point for Cohen and analyses of the concept of intention three of the themes that are sounded Levesque's two papers: "Persistence, to algorithms for recognizing plans, in Intentions in Communication: (1) Intention, and Commitment" and from logical formalizations of speech foundational work on intention and "Rational Interaction as the Basis of acts to analyses of intonational contours its relation to speech act theory, (2) Communication."

A fundamental question in AI is what mechanisms suffice for computer programs to make scientific discoveries. My Ph.D. thesis addresses this question by automating the following scientific task to a significant extent: Given observed data about a particular chemical reaction, discover the underlying set of reaction steps from starting materials to products, that is, elucidate the reaction pathway.

I give an introduction to Bayesian networks for AI researchers with a limited grounding in probability theory. Over the last few years, this method of reasoning using probabilities has become popular within the AI probability and uncertainty community. Indeed, it is probably fair to say that Bayesian networks are to a large segment of the AI-uncertainty community what resolution theorem proving is to the AIlogic community. Nevertheless, despite what seems to be their obvious importance, the ideas and techniques have not spread much beyond the research community responsible for them. This is probably because the ideas and techniques are not that easy to understand. I hope to rectify this situation by making Bayesian networks more accessible to the probabilistically unsophisticated.

Letters to the Editor

The design constructs about the functional aspects of these can be no more general than the Reviewed by Amit Mukerjee prototypes. A harbinger of actions, information that can then be learning and vocabulary inadequacy) change is perhaps the book Knowledge-Based used to refine or adapt the prototype may be why the authors turn to analog Design Systems by R. D. to meet the design goals. Coyne, M. A. Rosenman, A. D. Radford, problem is then reduced to the problem Where the book falls short is in M. Balachandran, and J. S. Gero of searching through these possible illustrating the difference between (Addison Wesley, Reading, Mass., control actions to identify a the design task and other traditional 1990, 567 pages): It presents the sequence that will result in the desired Much of the discussion concentrates view because the volume is based on techniques are used in this process. Some of the other problems encountered here will also planning-type search through a space issues that one would have thought be different. Indeed, it seems in vision, planning, learning, and so resulting in conflicting criteria that clear that a large number of design on.

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.

Letters to the Editor

In Memorium: Jonathan J. King (1949-1991)