A key data source available to FINCEN is reports of large cash transactions made to the Treasury according to terms of the Bank Secrecy Act. FAIS's unique analytic power arises primarily The most common motivation for criminal behavior is profit. The larger the criminal organization is, the greater the profit. By disrupting the ability to profit, law enforcement can focus on a vulnerable aspect of large criminal organizations. Money laundering is a complex process of placing the profit, usually cash, from illicit activity into the legitimate financial system, with the intent of obscuring the source, ownership, or use of the funds.

During the past year, a prototype expert system for tactical data fusion has been under development This compute1 program combines various messages concerning electronic intelligence (ELINT) to aid in decision making concerning enemy actions and intentions The prototype system is written in Prolog, a language that has proved to be very powerful and easy to use for problem/rule development The resulting prototype system (called EXPRS - Expert PRolog System) uses English-like rule constructs of Prolog code This approach enables the system to generate answers automatically to "why" a rule fired, and "how" that rule fired In addition, a rule clause construct is provided which allows direct access to Prolog code routines This paper describes the structure of the rules used and provides typical useI interactions IN THE MODERN MILITARY ENVIRONMENT, Multiple sensor inputs need to be interpreted in a timely manner to assess developing battlefield conditions. The high volume of data from such sensor systems, as well as their high rate of data transfer, make this timely interpretation difficult and very demanding of human resources. THE AI MAGAZINE Summer 1984 37 is inherently probabilistic as well as time varying and nonmonotonic. The fusion process can also require numerical analysis to be done on the raw sensor data. This "number crunching" analysis is best done (and is currently being done) with languages such as This form of representation is very general, offering good future growth potential for the system.

The Third International Workshop on Human and Machine Cognition was held in Seaside, Florida, on 13-15 May 1993. Each paper session included presentations on cognitive research, educational research, AI theory and logic, and particular knowledge engineering projects. This mixture encouraged the participants from diverse disciplines to listen and respond to one another. These international workshops are held to allow leading scientists, scholars, and practitioners to discuss current issues and research in particular topics in AI and cognitive science. These international workshops are held every other year to allow leading scientists, scholars, and practitioners to discuss current issues and research in particular topics in AI and cognitive science. This third workshop was supported by the University of West Florida; the West Florida Regional Medical Center; Taylor and Francis Publishing; John Wiley and Sons Publishers; the American Association for Artificial Intelligence; and the ...

Expert Systems: Where Are We? And Where Do We Go From Here? This article has benefited from careful readings by and suggestions from Mike Brady, Bruce Buchanan, Ed Feigenbaum, Jo& Gon&lez, Pete Szolovits, and Pat Winston Editor's note: This article was the author's "Invited Lecture" at IJCAI 7 Where has the Accepted Wisdom succeeded? One important goal of this part of the journey will be to calibrate the current state of the art-Given what we know, what can we do and how quickly can we do it? Does building a system typically require several months or several years?

Expert Systems: How Far Can They Go? A panel session at the 1985 International Joint Conference on Artificial Intelligence in Los Angeles dealt with the subject of knowledge-based systems; the session was entitled "Expert Systems: How Far Can They Go?" The panelists included Randall Davis (Massachusetts Institute of Technology); Stuart Dreyfus (University of California at Berkeley); Brian Smith (Xerox Palo Alto Research Center); and Terry Winograd (Stanford University), chairman. Part 1 of this article, which appeared in the Spring 1989 issue, began with Winograd's original charge to the panel, followed by lightly edited transcripts of presentations from Winograd and Dreyfus. Part 2 begins with the presentations from Smith and Davis and concludes with the panel discussion. Although almost four years have passed since this discussion took place, the issues raised and the points discussed appear no less relevant today.

How Far Can They Go? A panel session at the 1985 International Joint Conference on artificial intelligence in Los Angeles dealt with the subject of knowledge-based systems; the session was entitled "Expert Systems: How Far Can They Go?" The panelists included Randall Davis (Massachusetts Institute of Technology); Stuart Dreyfus (University of California at Berkeley); Brian Smith (Xerox Palo Alto Research Center); and Terry Winograd (Stanford University), chairman. The article begins with Winograd's original charge to the panel, followed by lightly edited transcripts of the panel's remarks. Part 1 includes presentations from Winograd and Dreyfus. Part 2, which will appear in the Summer 1989 issue, includes presentations from Smith and Davis and concludes with the panel discussion.

Editors' Note: In this provocative article Doyle suggests that I thank Jaime Carbonell, John McDermott, Joseph Schatz, and Derek Sleeman for helpful discussions and comments This research was supported by the Defense Advanced Research Projects Agency (DOD), ARPA Order No. 3597, monitored by the Air Force Avionics Laboratory under Contract F33615-81-K-1539. The views and conclusions contained in this document are those of the author, and should not be interpreted as representing the official policies, either expressed or implied, of the Defense Advanced Research Projects Agency or the Government of the United States of America Abstract, Knowledge engineers qualified to build expert systems are currently in short supply The production of useful and trustworthy cxpcrt systems can he significantly increased by pursuing the idea of nrCiculate ayprentzce.ship This revolution is very important. We now actively seek out tasks for automation that would never have been considered previously. It seems clear that the work of our society and industry includes many economically important (if often mundane) tasks whose automation may be possible with the new techniques.

Artificial Intelligence is solving more and more real world problems, but penetration into the complexities of government administration has been minimal. The author suggests that combining expert system technology with conventional procedural computer systems can lead to substantial efficiencies. Business rules can be removed from business-oriented computer systems and stored in a separate but integrated knowledge base, where maintenance will be centralized. Fourteen specific practical applications are suggested. Traditionally, these systems have been used to automate the accounting function, automate labor-intensive activities, manage and control vast financial and physical assets, process payrolls for hundreds of thousands of employees, and merge and summarize information about a wide set of activities in support of management decision making.

Human error is an increasingly important and addressable concern in modernday high-technology accidents. Avoidable human errors led to many famous accidents, including Bhopal, the space shuttle Challenger, Chernobyl, the Exxon Valdez, and Three Mile Island. Many hundreds of thousands of nonfamous accidents occur each year that are equally or more avoidable. Dramatic examples make the local headlines, such as car crashes, train and plane wrecks, and military-related operations mishaps. Less dramatic consequences happen even more frequently because of millions of mundane errors that appear daily in the products we use (for example, poorly designed cars), the processes we are affected by (for example, banking or healthcare institutions), and the automation that surrounds us (for example, unfriendly computers that expect us to adapt to their interfaces).

The enterprise of developing knowledge-based systems is currently witnessing great growth in popularity. The utility of a well-stocked store of examples and the ability to generate new examples are emphasized. Section 3 displays a wide variety of rule operations in addition to the rule interpreter which applies rules. It includes an argument that systems must be designed to respond well to forces of change. Speech on Artificial Intelligence delivered to the Canadian Information Processing Society, Session '84, Calgary, Alberta An earlier version of this article was published in the Proceedings of the CIPS/Session '84 This article was written while the author was with Rutgers Univcrsity Revision of draft performed at BBN Laboratories Research reported here was supported by NSF Grants Knowledge based systems may be usefully viewed in terms of three interrelated spaces.