Conference Report A1 field looks to the future: AAAI ’96, Portland, 4-8 August 1996

David Blanchard PO Box 759, Kent, OH 44240, USA Tel: + 7 (330) 677-4270 Fax: + 7 (3301 678-90 7 7 E-mail: blanchard@lionhrtpub.com WWW: http://lion hrtpu b. com

One sure sign that the artificial intelligence field has finally come of age is when its proponents pause to reflect on where they’ve been just long enough to chart out a course for where they’d like to go next. This past summer, the 13th National Conference on A1 (AAAI ’96), held in Portland, Oregon, looked at both the successes and the failures of the past 40 years’ worth of research. The pursuit of machine intelligence has found appeal with those of a theoretical bent as well as those devoted to real-world applications, and AAAI ’96 offered a glimpse as to where the A1 field will be headed into the next century.

In fact, the keynote presentation was delivered by Freder- ick Hayes-Roth, CEO of Teknowledge (Mountain View, California). Hayes-Roth was a fitting choice as keynote speaker since he’s been involved with both research and commercial products for many years. Teknowledge, for those without long memories, was one of the very first com- panies to commercialize an expert system shell, back in the 1980s. Despite its early success, Teknowledge virtually vanished from the scene when it was acquired by American Cimflex, a manufacturer of flexible assembly systems. Hayes-Roth decided to remain with the skeleton crew still involved with expert system research, and eventually his persistence paid off. The Cimflex connection eventually disappeared, Teknowledge is once again making a name for itself as a supplier of expert system development tools, and Hayes-Roth is now head of the company. So he’s had first-hand knowledge of what works and what doesn’t when

it comes to AI. ‘The A1 field should be able to achieve continuous, incremental progress,’ Hayes-Roth observed at AAAI ’96. He proceeded to list some of the proven intelli- gent technologies, such as representation (languages, domain modeling, knowledge engineering), inference (theorem-proving, heuristic reasoning, matching techniques), control (search algorithms, scheduling, demons, etc.), and problem-solving architectures (rule- based, frame-based, constraint-based, blackboard, object- oriented, etc.).

These technologies, Hayes-Roth pointed out, have led to a number of success stories for the A1 field, such as speech recognition systems, autonomous and tele-operated vehicles, various domain-specific planning and scheduling systems, hundreds of case-based assistants, and thousands of domain-specific expert systems. However, successful intelligent systems all seem to suffer from the same limi- tation: they’re not reusable. Intelligent systems tend to be expensive to develop, are focused on a specific task within a single domain, and are highly customized.

‘The scope of knowledge incorporated to date is too small,’ Hayes-Roth explained. Individual projects succeed, and succeed quite well, but these individual projects cannot be combined to compose systems of wider scope and capa- bility. ‘We must find a way to integrate across tasks,’ he urged. The principal strategy for developing the next gener- ation of intelligent systems, according to Hayes-Roth, should emphasize:

context-adaptable building blocks, reusable knowledge, high-value component functions,

architecture for semantic interoperability, composition architecture for multi-task systems,

and a small number of domains, which should be attacked persistently.

Where do we go from here?

AAAI ‘96 also hosted a panel of A1 experts, who each set forth specific challenges for the A1 field as a whole to tackle. For instance MIT’s Rodney Brooks, one of the lead- ing artificial life researchers, asked, ‘Can we build a pro- gram which can install itself and run itself on an unknown architecture? How about a program which can probe an unknown architecture from a known machine and recon- figure a version of itself to run on the unknown machine?’ And ultimately, ‘Can we build a system by evolution that is better at a non-trivial task than anything that has been built by hand?’ Nils Nilsson, with Stanford University, challenged robotics developers to create a robot that can

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perform ‘any task that a human might ‘reasonably’ expect it to be able to perform given its effodsensor suite. [And] the robot must stay on-the-job and functioning for a year without being sent back to the factory for re-programming.’

Tom Mitchell with Carnegie Mellon University wants to see programs built that turn the World Wide Web into the world’s largest knowledge base. ‘The challenge is to build programs that can ‘read’ the Web and turn it into, say, a frame-based symbolic representation that mirrors the con- tent of the Web.’ ‘Furthermore’, he urged, ‘let’s build agents that exhibit life-long machine learning, rather than machine learning algorithms that learn one thing and then get rebooted.’ He’d also like to see the field apply machine learning to learn to understand natural language.

Eric Horvitz from Microsoft had a challenge for his fel- low software developers: develop ‘comprehensive auton- omous decision-making systems that are situated in dynamic environments over extended periods of time, and that are entrusted with handling varied, complex tasks.’

Thomas Dean from Brown University issued a challenge ‘to theorists, experimentalists and practitioners alike to raise the level of expectation for collaborative scientific research in planning.’ As far as Dean is concerned, what the A1 field needs in order to thrive is a common sense of community that places equal value on the efforts of the laboratory research and the corporate hacker upgrading a commercial development tool.

The remarkable has become routine

In keeping with the forward-looking attitude prevalent at AAAI ’96, the Innovative Applications of A1 (IAAI ’96) conference also paused long enough to chart a new course. The IAAI show has been sponsored by AAAI since 1989, and a conservative estimate of the savings and enhanced earnings made possible by the 150-odd intelligent systems profiled at IAAI over the years is well in excess of a billion dollars. Using any measurement gauge, the IAAI has dem- onstrated the tremendous successes that have been achieved with intelligent systems.

Nevertheless, there is some concern among the IAAI organizers that as intelligent systems continue to be developed and deployed, the public at large will no longer see anything remarkable about A1 technology. Once the impossible does indeed become possible, it then becomes mundane and routine. One of the shortcomings of the IAAI show as a whole, according to Howard Shrobe of the MIT A1 Lab and co-chair of IAAI ’96, is that the applications haven’t demonstrated much new research, with the excep- tion of a handful of case-based reasoning systems. The plan for future conferences will be to integrate both the AAAI and the IAAI shows into one larger conference with several tracks, focusing on the interaction between research and applications. The IAAI shows will particularly look at

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enabling technologies, examine application insights and highlight emerging applicable research efforts.

Following are the 18 IAAI ’96 applications and their developers:

AdjudiPro 2.0, United Healthcare Corp. Balance Sheet Estimation Tool (BALET), Swiss Bank Bounced Mail Expert System (BMES), The White House Office of Media Affairs CemQUEST, Schlumberger Cambridge Research Comet, Price Waterhouse Technology Center Expert Authorizations System (EASY), Equifax Check Services EZ Reader, Chase Manhattan Bank Global Scale Help Desk, Reuters America Knowledge Acquisition and Rule Management Assist- ant (KARMA), Federal National Mortgage Associ- ation Monitoring Frog Communities, University of Mel- bourne, University of New South Wales, and Univer- sity of Queensland NASA Personnel Security Processing Expert System, NASA Performance Expert (PERFEX), GTE Laboratories Roll-Cutter, Bull HN Settlement Analysis Expert (SAX), Frito-Lay SIGNAL Expert System, SIGNAL Group Special Service Circuit Fault Isolation (SSCFI), GTE Laboratories Supply Chain Integrated Ordering Network (SCION), J. Sainsbury Trouble Localization Module. Pacific Bell

Virtual reality at Boeing In addition to the above-named innovative applications, AAAI ’96 also offered a look at a system that uses techno- logies not normally associated with A1 shows, - virtual reality application from airplane manufacturer Boeing (Seattle, Washington). Boeing has developed FlyThru, a digital pre-assembly system for checking designs. Using FlyThru, a spin-off of a Boeing advanced computing re- search project, engineers are able to view up to 1500 mod- els in 3-D at high speed. This virtual reality system was first deployed a few years ago to meet the needs of the Boeing 777 aircraft for large-scale product visualization and verification.

According to Bob Abarbanel, with Boeing’s Infor- mation & Support Services, the digital pre-assembly pro- cess has met with very favorable results. ‘The 777 has had far fewer assembly and systems problems compared to pre- vious airplane programs,’ Abarbanel reported.

Today, FlyThru is installed on hundreds of workstations on almost every airplane program, according to Abarbanel, and is being used on Space Station, F22, AWACS, and other defence projects. ‘In many ways, FlyThru is a data

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warehouse supported by advanced tools for analysis,’ he explained. The system is currently being integrated with knowledge-based engineering geometry generation tools.

Vendor roundup

It’s no secret that the AAAI exhibitions ‘ain’t what they used to be’. Ten thousand attendees used to flood the show floors, looking with wonder upon the lavish booths spon- sored by the likes of major hardware vendors such as IBM, Digital Equipment, Sun Microsystems, Hewlett-Packard, Apple Computer, and Symbolics (remember them?) For the past several years, though, the AAAI trade show has been a smaller, quieter affair, focusing on software innovations and reflecting the current interest in robotics (the annual robot competitions at AAAI continue to be very popular).

Following are capsule summaries of the products exhi- bited the major AAAI ‘96 vendors:

Angoss Software International (Toronto, Ont., Canada) displayed its Knowledgeseeker IV data mining pro- duct, a knowledge discovery and prediction tool. Attar Software (Harvard, Mass.) exhibited three of its intelligent data mining software tools: Analyzer, which uses probabilistic rule induction, genetic algor- ithms and neural networks; Profiler, which exploits SQL servers and massively parallel processors, and XpertRule, which combines inductive knowledge acquisition, genetic algorithms, fuzzy logic and rule- based technology. Franz (Berkeley, Calif.) demonstrated the benefits of its dynamic object-oriented software technology, based on Common Lisp. Harlequin (Cambridge, Mass.) debuted its new Adapt- ive Systems Group, which will provide consulting ser- vices in the fields of intelligent agents, modem decision theory, operational research, and Bayesian inferencing. The company also exhibited its dynamic object-oriented development toolkits such as Script- Works, Watson and Webmaker. Intelligent Automation (Rockville, Md.) displayed a number of products, including Cybelle, an intelligent

agent infrastructure; Rotoscan, a ballistic analysis sys- tem; ASAT, an automated qualitative tool; MIDIS, a concurrent engineering tool for designing electronic circuits, and MDSP-200, a digital signal processor for adaptiveheural network control. Isoft (Gif sur Yvette, France) exhibited its intelligent software tools, including AC2, a decision tree-based data mining development environment; ALICE, a data mining tool with advanced reporting features, and Recall, an integrated case-based reasoning tool. Nomadic Technologies (Mountain View, Calif.) pre- viewed its next-generation robot concept, the Nomad S8, which employs advances in mobility, sensing and multiprocessor networks. Real World InterfaceIActivMedia (Jaffrey, N.H.) develops mobile robotic platforms, and exhibited its B14, B21 and Pioneer mobile systems. Triodyne (Niles, Ill.) is commissioned by the U.S. Department of Energy to develop new technology for environmental clean-up, waste management and related areas. WizSoft (Tel Aviv, Israel) exhibited its WizWhy software, which uses data mining techniques to predict outcomes for new cases.

Attendance at AAAI ’96 (which includes the IAAI show, a conference on Knowledge Discovery and Data Mining, and the robotic competition) was 1,500, a large drop-off from the 3,000 who attended the International Joint Confer- ence on A1 (IJCAI ‘95) last year in Montreal. Since the previous AAAI show (AAAI ‘94) was held just up the interstate from Portland in Seattle, the AAAI has probably worn out its welcome in the American Northwest. Wisely, next year’s show will be held in Providence, R.I., just out- side of Boston, one of the hotbeds of A1 research.

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David Blanchard is editor-in-chief of Lionheart Pub- lishing’s Newsletter Division (Kent, Ohio). He has written Intelligent Systems Report, a monthly news- letter about the A1 field, since 1988.

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