Reports from some of these first projects make up the majority of the book, with the balance of the book providing an overview of neuroinformatics. The book's foreword provides interesting history and perspective on the incubation of neuroinformatics. The preface and first two chapters of the book explain neuroinformatics and the motivation for it. As with so many other fields, there has been an information explosion in neuroscience research. Data are produced by tens of thousands of investigators in hundreds of journals.

The Fourth International Conference on Autonomous Agents took place in Barcelona (Catalonia, Spain) from 3 to 7 June 2000, the first one held outside the United States. It had a similar attendance to previous years (435 attendees), thus opening the possibility of other conferences outside the United States. The program committee chairs were Maria Gini, the University of Minnesota, and Jeff Rosenschein, the Hebrew University in Israel. There were 199 submissions from 20 countries, from which 48 papers and 65 posters were selected. Gini managed to obtain some key sponsorship from the Defense Advanced Research Projects Agency (DARPA) and the National Science Foundation to support the travel expenses of more than 25 U.S. students.

Picture tactile feedback and situated computing. That's the year when a revolving cadre of scientists began work on the problem of predicting the outcome of the spin of a roulette wheel. Although lacking the societal import of, say, predicting cancer in a patient, or even poison in a mushroom, predicting roulette seems on the face of it of even greater difficulty. The game itself is designed in every way for unpredictability. The problem is at its core a machine learning problem with a direct physical basis.

The First National Aeronautics and Space Administration (NASA) Workshop on Monitoring and Diagnosis was held in Pasadena, California, from 15 to 17 January 1992. The workshop brought together individuals from NASA centers, academia, and aerospace who have a common interest in AIbased approaches to monitoring and diagnosis technology. The workshop was intended to promote familiarity, discussion, and collaboration among the research, development, and user communities. The First National Aeronautics and Space Administration (NASA) Workshop on Monitoring and Diagnosis was held in Pasadena, California, from 15 to 17 January 1992. The workshop was hosted by the Jet Propulsion Laboratory (JPL) and took place at the Ritz-Carlton Huntington Hotel.

Department of Computer Science Carnegae-Mellon Unaverszty P&burg, PA 15213 Editors' Note: Many expert systems require some means of handling heuristic rules whose conclusions are less than certain Baysian techniques and other numerical scoring methods have been developed to combine and propagate certainty measures as the expert system draws inferences in solving different problems. Doyle's paper argues that it is difficult for a human expert to produce reliable probabilities or numerical scoring factors for an inference rule, and that a radically different approach to the problem should be considered He essentially suggests that the expert be encouraged to think in terms of specific instances which would conflict with the general rule and to encode this knowledge explicitly. Methodologically this seems to be very appealing, and helps to make both explicit and rigorous some of the techniques currently used by knowledge engineers whm they encode and refine the expert's knowledge We would welcome comments and criticisms of this approach from those steeped in the practical issues of constructing large rule-based expert systems. Probabilistic rules and their variants have recently supported several successful applications of expert systems, in spite of the difficulty of committing informants to particular conditional probabilities or "certainty factors," and in spite of the experimentally observed insensitivity of system performance to perturbations of the chosen values Here we survey recent developments concerning reasoned assumptions which offer hope for avoiding the practical elusiveness of probabilistic rules while retaining theoretical power, for basing systems on the information unhesitatingly gained from expert informants, and reconstructing the entailed degrees of belief later @

Review of The Mind Doesn't Work That Way: The Scope and Limits of Computational Psychology If you are interested in writing a review, contact chandra@ cis.ohio-state.edu. AT question: Which one of the following doesn't belong with the rest? It is the only discipline in the list that is not under attack for being conceptually or methodologically confused. Objections to AI and computational cognitive science are myriad. Accordingly, there are many different reasons for these attacks. However, all of them come down to one simple observation: Humans seem a lot smarter than computers--not just smarter as in Einstein was smarter than I, or I am smarter than a chimpanzee, but more like I am smarter than a pencil sharpener. To many, computation seems like the wrong paradigm for studying the mind. All this is because of another truth: The computational paradigm is the best thing to come down the pike since the wheel. The Mind Doesn't Work That Way: The Scope and Limits of Computational Psychology, Jerry Fodor, Cambridge, Massachusetts, The MIT Press, 2000, 126 pages, $22.95. Jerry Fodor believes this latter claim. He says: [The computational theory of mind] is, in my view, by far the best theory of cognition that we've got; indeed, the only one we've got that's worth the bother of a serious discussion.… There is, in short, every reason to suppose that Computational Theory is part of the truth about cognition. It is a fascinating read. This dispute about quantity of truth is where the book gets its title. In 1997, Steven Pinker published an important book describing the current state of the art in cognitive science (see also Plotkin [1997]). Pinker's book is entitled How the Mind Works. In it, he describes how computationalism, psychological nativism (the idea that many of our concepts are innate), massive modularity (the idea that most mental processes occur within a domain-specific, encapsulated specialpurpose processor), and Darwinian adaptationism combine to form a robust (but nascent) theory of mind. Fodor, however, thinks that the mind doesn't work that way or, anyhow, not very much of the mind works that way. Fodor dubs the synthesis of computationalism, nativism, massive modularity, and adaptationism the new synthesis (p.

The Second International Conference on Conceptual Structures (ICCS'94) was held at the University of Maryland on August 16 to 20. The conference, which marked the tenth anniversary of conceptual graphs, was attended by about 80 scientists from 12 countries. This article presents some of the conference highlights. The conference marked the tenth anniversary of conceptual graphs. About 80 scientists from 12 countries attended.

Toward thi: end, knowledge acquisition is sometimes considered a nccessary burden, carried out under protest so that one can gel on with t,he study of cognitive processes in problem solving In this article we argue that, t,he two activities-knowledge acqisitSion and cognitive modeling-are necessarily interwoven, and provide interesting opportunities when t,akcr Logether. Knowledge acquisition shapes cognit,ive modeling because operatzonnl knowledge cont,ains assurnpt,ions nnc directions for its use, t,hat, is, a.11 implicit, processing model In return, problem solving models can profoundly shape knowledge acquisition by providing a framework for the articulation and creation of domain expertise This int,rodllces the theme of this article, t,hat, one can engzneer bodie: of knowledge for various purposes, such as learnability, To the knowledge engineering slogan "knowledge is power," we add "knowledge is an artifact,, worthy of design " The organization of this article is as follows: We first consider the pract,ice of "cognitive advantage " III the t,hird section we suggest some A Shift in Viewpoint from Experts to Clans Over the past decade t,hcrc have been trcmcndous advances in the fabrication of integrated circuits (Robinson, 1980a). Circuits have become smaller and manufacturing costs have dropped dramatically. Design is becoming the dominant cost (Robinson, 19801) with the current round of miniaturization, which goes by the name of VLSI for very large scale integration. This is leading to a substantial int,crest in undcrst,anding design processes.

We thank Kaz Kulikowski and Priscilla Rasmussen of Rutgers Universitv for their areat helD in organization of the Workshop One of the particularly sat,isfying aspects of this Workshop was the attendance by a large number of graduate students and medical fellows active in AIM research; this was made possible by a generous grant, from AAAI Chris Putnam and OS17 AI graduate students worked very hard in t,aking care of a number of details. A nurnber of systems for medical decision making, experimenting with new ideas for knowledge organization and problem solving, have been built there. The College of Medicine has just started a center for research in knowledge-based systems in medicine. Thus, after a number of years when the Workshop had been hosted by the AIM groups of MIT, TJniversity of Pittsburgh, Rutgers, and Stanford, sometimes in conjunction with major AI and medical computiug conferences, holding the Workshop at Ohio State University was an indication of a broader base for research activities in AIM. This report gives an overview of the Workshop discussions, without any claim of being complete or even representative-a report, of this kind can only be an impressionistic account.

This report is a review of the First National Conference on Knowledge Representation and Inference in Sanskrit, Bangalore, India, 20 through 22 December, 1986 The conference was inspired by an article that appeared in the Spring 1985 issue of AI Magazine--"Knowledge Representation in Sanskrit and Artificial Intelligence." A working group has been created to pursue the goals of the conference and to possibly arrange another conference for 1987 and 1988 This conference is analogous to the consultation of philosophers and cognitive psychologists by computer scientists in the beginnings of AI. Western psychology and philosophy is quite different from the Indo-Aryan tradition: the former has its basis in Aristotelian logic and the scientific method, whereas the latter is also based on introspection and internal experience Nevertheless, both these schools have converged in the analysis of natural language and the extraction of the semantic message from a text.The purpose of AI in this context is to derive a "method" for natural language understanding; the purpose for the Sanskrit scholars was to understand the nature of language and thought in and of itself. Hence, for the Sanskrit scholars, the actual methodology was implicit; it was not the focus. The purpose of the conference was to extract this hidden "algorithm" of automatic semantic parsing from the Sanskrit pandits.