AI Magazine Volume 18 Number 4 (1997) (© AAAI)

that the working artifacts that have AAAI-97 Highlights been constructed are a milestone and transition point in the field. He cited as evidence a broad range of systems, Developments in the AI Field including a game-playing system that beat a world champion; heuristic scheduling systems that are faster than traditional approaches; decision-mak- Sara Hedberg ing expert systems in corporations, fi- nancial forecasting, robots, and vision systems; speech-recognition systems; and conversational agents. This historical, developmental ap- proach to AI was visible throughout the conference. During the overview t “is a privilege to do AI research at tions and progress in the field. The presented at the 1997 Mobile Robot the end of the twentieth century,” strong tutorial sessions, workshops, Competition, for example, time was Ibegan Benjamin Kuipers, program invited talks, the Innovative Applica- spent looking back over the first five cochair, during his opening remarks at tions of AI (IAAI) program, as well as competitions and the progress that the Fourteenth National Conference 72 technical sessions, demonstrated has been made in robot technology in on AI (AAAI-97) in Providence, Rhode the diverse activity going on under the such a few short years. Each year, the Island, this summer. “A computer beat AI umbrella. From intelligent agents to contestants at the annual Mobile the world champion at chess. A robot natural language, machine learning to Robot Competition get better, and the is on Mars making a few of its own de- reasoning and representation, the events get harder. This year, the events cisions.” Kuipers reminded us that number of technologies that are ma- were the most lifelike to date: Robots these accomplishments are the result turing is impressive. from the leading research laboratories competed in events to find a television of 40 years of research; AI is much old- AI Growing Up er than the technical sessions at this remote control, vacuum a home, pass The hall was packed for the keynote year’s conference. hors d’oeuvres at the conference re- address, “AI Growing Up,” by James F. This year’s conference not only cel- ception, and simulate finding life on Allen of the University of Rochester. ebrated AI’s visible achievements, not- Mars. More than 20 teams competed Allen deftly compared AI to the stages ed Kuipers. At its heart, it is a technical this year. of human development. First, he re- conference. It centers on the science minded the audience that AI is a very On the Shoulders of Giants and technology that grow into appli- young area—only 40 years old. In his This theme of AI growing up was most cations. admittedly idealized model, during dramatically driven home during the Attendees at this year’s conference human infancy-childhood, the em- award ceremony for the Deep Blue were privileged to witness the award- phasis is on developing basic skills team and the chess pioneers who ing of the Fredkin Prize to the IBM through creative exploration. During paved the way. Following the award Deep Blue team that defeated world adolescence, we develop a sense of ceremony, there was a series of presen- chess champion (see self-reliance, self-discipline, and habits tations that traced the progress of AI discussion to follow) as well as the for a lifetime. As adults, we refine and chess research. As Fredkin himself not- Allen Newell Research Excellence further develop ourselves, train future ed, a tremendous number of people Medal to the handful of AI research pi- generations, and attain a deep under- across the world pushed the technolo- oneers whose work led to Deep Blue’s standing of life. gy. It was clear that the Deep Blue victory. Allen asserted that AI has been in its team stood on the shoulders of giants Attendees also witnessed the first- childhood. The field now needs a bet- such as John McCarthy, Ken Thomp- ever reception with mobile robots ter sense of self and self-control. AI is son, and Hans Berliner. serving hors d’oeuvres to the guests. at a transition point, at a defining mo- The AI community lauded Deep They saw a robotic wheelchair that ment, according to Allen. There are Blue’s achievement of a long-standing was steered by the eye movements of working prototypes to support the ex- AI grand challenge—to be the first the rider. They watched computer periments, such as game playing, ex- machine to beat the games such as Scrabble and Go played pert systems, robots on Mars, and con- world chess champion. However, the by world-class human players in the versational agents. celebration went far beyond verbal ac- first Hall of Champions. The body of Allen’s talk focused on colades with the Fredkin Prize. In However, the conference was more defining AI, its goals and methodolog- 1980, Massachusetts Institute of Tech- than the formal achievements and ex- ical issues. He talked about the slip- nology Professor of Computer Science hibitions. It was once again the place pery slope of defining intelligence Edward Fredkin established a three- where the leading researchers in the from various disciplines such as educa- tier prize to stimulate research in com- field gathered to share research direc- tion and linguistics. He emphasized puter chess. The following year, the

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first $5,000 in prize money was given to two scientists from Bell Laboratories who built the first chess machine to achieve master status. Seven years later, in 1988, the sec- ond tier of the challenge was reached by a team of five graduate students from Carnegie Mellon University (CMU) who built the first machine to achieve international master status. The machine was called Deep Thought, the ancestor of Deep Blue. Soon thereafter, the team moved to IBM and has since been working un- der wraps on Deep Blue. Deep Blue stepped up to the third tier of the Fredkin Prize: The team was awarded the $100,000 purse by Fred- kin at AAAI-97 amid a highly enthusi- astic full house. Team members were also awarded the Allen Newell Re- The AAAI–97 Conference Reception was Held in the Exhibit Hall. search Excellence Medal, sponsored by CMU. Each of the major researchers maintenance plans, are given in the decisions; and can adapt the behavior who helped blaze the trail for Deep conference proceedings, available of the system to ever-changing cir- Blue was also presented with Allen from AAAI. cumstances. The system allows auto- Newell Medals: Richard Greenblatt for This year 11 applications received matic, semiautomatic, or manual scheduling modes. MACHACK VI; David J. Slate and the award: The Union Pacific Railroad–Bright- Lawrence R. Atkin for CHESS 4.7; Ken Computer diagnosis: Hewlett-Packard ware entry was for the scheduling of Thompson and Joe Condon for BELLE; and IBM were the two winners in this rail at Union Pacific Railroad. It plans Hans Berliner, Carl Ebeling, Gordon category. and schedules the production, packag- Goetsch, and for The Hewlett-Packard entry was PIM- ing, delivery, and pickup of rail for the HITECH; and Feng H. Hsu, Murray TOOL, an expert system to troubleshoot maintenance of 31,000 miles of rail- Campbell, Thomas Anantharaman, computer hardware failures. It diag- road track in 24 states. It produces Andreas Nowatzyk, and Mike Browne noses the cause of failure of a Hewlett- low-cost schedules that allocate re- for Deep Thought. Packard server. sources. AAAI-97 indeed brought together, The IBM entry was for the design of The Information Technology Insti- as Kuipers put it, many of the bricks in a high-performance help-desk applica- the wall of achievements that AI is tute entry was SUNRAY V, an intelligent tion and its implementation result. building. If, as Allen asserted, the field container trucking operations man- The remote expert system to optimize is at the point of a major transition, if agement and control system. It assists repair efficiency (restore) is deployed it is indeed entering the defining peri- a human planner in the complex at IBM in Rochester, Minnesota, to od of adolescence, then indeed there is scheduling of container trucks within support the as/400 business computer much to look forward to at AAAI-98, the constraints of the shipping agents, systems. It builds on a previous rule- AAAI-99, and beyond. customers, and the port. Deployed at based application, allowing quick and Conference proceedings and tapes one of the larger haulage companies, easy maintenance and changes to the of many of the sessions are available with a vehicle fleet of 30 towheads from the American Association for Ar- system. and 220 trailers, it handles about 500 tificial Intelligence (AAAI). Scheduling: Sistemas Cognitivos (Lis- jobs a day. bon, Portugal), Union Pacific Rail- Planning-Layout: Hyundai–Korea road–Brightware, and Information Advanced Institute of Science and 1997 IAAI Winners Technology Institute (Singapore) were Technology (KAIST) and La Caisse the three winners in this category. The IAAI award is given to deployed d’…pargne–Isoft (France) were the two The Sistemas Cognitivos entry was winners in this category. applications that use AI and are recog- CREWS_NS (scheduling train crew in the The Hyundai-KAIST entry was a nized for their innovative use of tech- Netherlands). It schedules the 5000 case- and constraint-based apartment nology and significant payback. De- drivers and guards of the Dutch rail- construction project planning system: tails of each application, including the ways. It is a “white box” system for the FASTRAK-apt builds plans for new pro- business problem it addresses, the ar- planner who can see what is going on; jects based on previous cases. chitecture, technology innovations, can interact with the scheduler, The La Caisse d’…pargne–Isoft en- development effort, payback, and proposing alternatives and querying try was STHANA, a profitability forecast

WINTER 1997 9 News

AAAI Past President Raj Reddy and Professor Ed Fredkin Pose with Fredkin Prize and Allen Newell Research Excellence Medal Recipients. and situation analysis system for auto- compliance in the chemical industry. prove the efficiency of processing a mated teller machines (ATMs). STHANA This knowledge-based system supports loan by reducing the time, paperwork, helps one of the major French banks, compliance with regulatory require- and associated cost with loan origina- La Caisse d’…pargne, manage 2500 ments for communicating health and tion. It processes loan applications ATMs all over France where the credit safety information in the shipping with incomplete, unverified, and con- card system makes it highly profitable and handling of chemical products. flicting information. The system gener- for banks to have high use of ATMs. It The case-based reasoner automatically ates a credit recommendation based on extracts information from existing da- generates estimates of hazard-related the loan’s conformity to credit stan- ta (economic, geographic, and inter- properties for every product. dards and an eligibility recommenda- nal bank data) from the bank’s ex- The New York State Department of tion based on the loan’s conformity to perts, builds up classifications on Education Office of Vocational and eligibility requirements. The system high-level descriptors from raw data, Educational Services for Individuals helps standardize the interpretation of and eventually indicates a measure of with Disabilities–Siena College entry underwriting guidelines. the ATM’s activity and profitability. was DISXPERT, a Social Security disabil- The Oxford Health Plans entry was The system highlights factors that ity screening expert system. It is an the PROVIDER SELECTION TOOL (PST). It as- could lead to higher profitability or expert system tool for referral of so- sists members of this managed health pinpoints the ATM’s vulnerabilities. cial security disability recipients to care plan in selecting a primary care Regulatory compliance–Eligibility vocational rehabilitation services. It physician. Deployed as a help desk determination: Air Products and enables paraprofessionals working as within Oxford and on the World Wide Chemicals, the New York State Depart- social caseworkers to assess and refer Web, it elicits search criteria from a ment of Education–Siena College, Fan- clients to rehabilitation services. member to assess and evaluate a roster nie May–Brightware, and Oxford The Fannie Mae–Brightware entry of doctors that meet these criteria. A Health Plans were the four winners in was the DESKTOP UNDERWRITER, Fannie case-based system, it is currently used this category. Mae’s automated mortgage-underwrit- approximately 700 times a day; 96 The Air Products and Chemicals en- ing expert system. Fannie Mae, the percent of those who use PST have their try was CHEMREG, using case-based rea- largest U.S. source of conventional needs met and have not called back soning to support health and safety mortgage funds, uses the system to im- with the same request.

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