AAAI-10 will be held in Atlanta, Georgia! Please mark your calendars, and visit www.aaai.org/Conferences/AAAI/ For more information on Human and Machine Cognition Chicago, please visit www.choose AAAI recently launched a series of (IHMC), is the sixth recipient of the chicago.com. The AAAI 2008 Teaching Forum aims 2006 and 2007 will continue in 2008, industry representative.

(ICEIS 2008). (ESAS 2008). Fax: 32-26502715 Faculty of Electrical Engineering and Email: ants@iridia.ulb.ac.be Computing, University of Zagreb URL: iridia.ulb.ac.be/ants2008/ Submission requirements may vary for each workshop, but most Multidisciplinary Workshop on Advances in Preference Handling conform to the schedule below.

The eighteenth annual International Workshop on Principles of Diagnosis was held in Nashville, Tennessee, May 29–31, 2007. Papers presented at the workshop covered a variety of theories, principles, and computational techniques for diagnosis, monitoring, testing, reconfiguration, fault-adaptive control, and repair of complex systems. This year’s workshop emphasized inter-actions and exchange of ideas and experiences between researchers and practitioners whose backgrounds included AI, control theory, systems engineering, software engineering, and related areas.

The Kiva warehouse-management system creates a new paradigm for pick-pack-and-ship warehouses that significantly improves worker productivity. The Kiva system uses movable storage shelves that can be lifted by small, autonomous robots. By bringing the product to the worker, productivity is increased by a factor of two or more, while simultaneously improving accountability and flexibility. A Kiva installation for a large distribution center may require 500 or more vehicles. As such, the Kiva system represents the first commercially available, large-scale autonomous robot system. The first permanent installation of a Kiva system was deployed in the summer of 2006.

Our work is aimed at enabling a new style of virtual, distributed scientific research. We have designed, built, and deployed an interdisciplinary virtual observatory—an online service providing access to what appears to be an integrated collection of scientific data. The Virtual Solar-Terrestrial Observatory (VSTO) is a production semantic web data framework providing access to observational data sets from fields spanning upper atmospheric terrestrial physics to solar physics. The observatory allows virtual access to a highly distributed and heterogeneous set of data that appears as if all resources are organized, stored, and retrieved or used in a common way. The end-user community includes scientists, students, and data providers. We will introduce interdisciplinary virtual observatories and their potential impact by describing our experiences with VSTO. We will also highlight some benefits of the embedded semantic web technology and also provide evaluation results after the first year of use.

In this editorial we introduce the articles published in this special AI Magazine issue on innovative applications of artificial intelligence. Discussed are a pick-pack-and-ship warehouse-management system, a neural network in the fishing industry, the use of AI to help mobile phone users, building business rules in the mortgage lending business, automating the processing of immigration forms, and the use of the semantic web to provide access to observational datasets.

This article describes the architecture and AI technology behind an XML-based AI framework designed to streamline e-government form processing. The framework performs several crucial assessment and decision support functions, including workflow case assignment, automatic assessment, follow-up action generation, precedent case retrieval, and learning of current practices. To implement these services, several AI techniques were used, including rule-based processing, schema-based reasoning, AI clustering, case-based reasoning, data mining, and machine learning. The primary objective of using AI for e-government form processing is of course to provide faster and higher quality service as well as ensure that all forms are processed fairly and accurately. With AI, all relevant laws and regulations as well as current practices are guaranteed to be considered and followed. An AI framework has been used to implement an AI module for one of the busiest immigration agencies in the world.

The mobile Internet represents a massive opportunity for mobile operators and content providers. Today there are more than 2 billion mobile subscribers, with 3 billion predicted by the end of 2007. However, despite significant improvements in handsets, infrastructure, content, and charging models, mobile users are still struggling to access and locate relevant content and services. An important part of this so-called content-discovery problem relates to the navigation effort that users must invest in browsing and searching for mobile content. In this article we describe one successfully deployed solution, which uses personalization technology to profile subscriber interests in order to automatically adapt mobile portals to their learned preferences. We present summary results, from our deployment experiences with more than 40 mobile operators and millions of subscribers around the world, which demonstrate how this solution can have a significant impact on portal usability, subscriber usage, and mobile operator revenues.

Custom DU is an automated underwriting system that enables mortgage lenders to build their own business rules that facilitate assessing borrower eligibility for different mortgage products. Developed by Fannie Mae, Custom DU has been used since 2004 by several lenders to automate the underwriting of numerous mortgage products. Custom DU uses rule specification language techniques and a web-based, user-friendly interface for implementing business rules that represent business policy. By means of the user interface, lenders can also customize their underwriting findings reports, test the rules that they have defined, and publish changes to business rules on a real-time basis, all without any software modifications. The user interface enforces structure and consistency, enabling business users to focus on their underwriting guidelines when converting their business policy to rules. Once lenders have created their rules, loans are routed to the appropriate rule sets, and customized, but consistent, results are always returned to the lender. Using Custom DU, lenders can create different rule sets for their products and assign them to different channels of the business, allowing for centralized control of underwriting policies and procedures—even if lenders have decentralized operations.

A generic image learning system, CogniSight, is being used for the inspection of fishes before filleting offshore. More than 30 systems have been deployed on seven fishing vessels in Norway and Iceland over the past three years. Each CogniSight system uses four neural network chips (a total of 312 neurons) based on a natively parallel, hard-wired architecture that performs real-time learning and nonlinear classification (RBF). These systems are trained by the ship crew using Image Knowledge Builder, a ”show and tell” interface that facilitates easy training and validation. Fishers can reinforce the learning anytime when needed. The use of CogniSight has significantly reduced the number of crew members needed on the boats (by up to six persons), and the time at sea has been shortened by 15 percent. The fast and high return of investment (ROI) to the fishing fleet has significantly increased the market share of Pisces Industries, the company integrating CogniSight systems to its filleting machines.