Case-Based Reasoning
Introduction to the IAAI Articles in This Issue
In this and the next issue of AI Magazine, we will present extended versions of papers presented at IAAI-12 (held in Toronto, Ontario, Canada) that were selected for their description of AI technologies that are either in practical use or close to it. We also present an article by Ramon Lopez de Mantaras based on his 2011 Robert S. Engelmore Memorial Lecture. Our selections for this issue begin with Playing with Cases: Rendering Expressive Music with Case-Based Reasoning by Ramon Lopez de Mantaras and Josep Lluís Arcos, based on the Robert S. Engelmore Memorial Lecture at IAAI-11 in San Francisco, California. Lopez de Mantaras received the Robert S. Engelmore Memorial Lecture Award for his pioneering research contributions in a breadth of artificial intelligence areas, especially pattern recognition and case-based reasoning, leading to novel applications in design, diagnosis, and music, and for extensive international leadership and service for the AI community. He is also a founding member of several AI companies.
Developing and Deploying Knowledge on a Global Scale
Reuters is a worldwide company focused on supplying financial and news information to its more than 40,000 subscribers around the world. To enhance the quality and consistency of its customer-support organization, Reuters embarked on a global knowledge development and reuse project. The resulting system is in operational use in North America, Europe, and Asia. The system supports 38 Reuter products worldwide. This article presents a case study of Reuter experience in putting a global knowledge organization in place, building knowledge bases at multiple distributed sites, deploying these knowledge bases in multiple sites around the world, and maintaining and enhancing knowledge bases within a global organizational framework.
Introduction to the IAAI Articles in This Issue
In this issue of AI Magazine, we continue our presentation of extended versions of papers presented at IAAI-12 (held in Toronto, Ontario, Canada) that were selected for their description of AI technologies that are in practical use. Our selections for this issue describe deployed applications. They explain the context, requirements, and constraints of the application, how the technology was adapted to satisfy those factors, and the impact that this innovation brought to the operation in terms of cost and performance. The articles also supply useful insights into use cases that we hope can also be translated to other work that the AI community is engaged in. In the first of these deployed application articles, eBird: A Human/Computer Learning Network to Improve Biodiversity Conservation and Research by Steve Kelling, Carl Lagoze, Weng-Keen Wong, Jun Yu, Theodoros Damoulas, Jeff Gerbracht, Daniel Fink, and Carla Gomes, the authors describe an intriguing application that successfully combines the best in human and artificial computing capabilities with an active feedback loop between people and machines.
Articles
We give a brief outline of key issues and a summary of the various different approaches taken by participants in the research field. The outlook is optimistic: a lot has been achieved in 10 years. When heckled, professional comedians frequently lament that "everyone's a comedian!" It's easy to see why: professional comedians don't possess different kinds of brains from others or engage in radically different kinds of behaviors from others, and moreover, the success of their acts is predicated on others' shared ability to understand and reason about comic situations they describe. The difference between comedians and their audience is a matter not of kind, but of degree, a difference that is reflected in the vocational emphasis they place on humor.
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Using Case-Based Reasoning to Support Health and Safety Compliance in the Chemical Industry
Implementation of the case-based reasoner in rules and objects using a commercial knowledge-based system shell is described. Although some refinements remain, the performance of the case-based reasoner has met its design goals. The chemical industry is heavily regulated. Every hazardous chemical product must have a set of shipping descriptions that conform to strict regulations issued by the Department of Transportation (DOT), the International Maritime Organization (IMO), and the International Air Transport Association (IATA). Shipping descriptions provide a concise characterization of the hazards a chemical can present during transportation (figure 1). Failing to comply with transport regulations can result in penalties ranging from delayed shipments to heavy fines or even incarceration of corporate officials. In addition, each chemical product has a material safety data sheet (MSDS) that conforms to Occupational Safety and Health (OSHA) and American National Standards Institute (ANSI) standards. Unlike shipping descriptions, MSDSs are lengthy documents of 8 to 10 pages that provide a detailed description of the health hazards a product can pose in the workplace (figure 2). They also contain information on procedures for storing, handling, and disposing of a chemical. Inadequately prepared MSDSs can lead to substantial product-liability lawsuits against the company if the product is involved in an industrial accident. The ultimate goal of these regulations is to ensure proper communication of health and safety information for the protection of the public. Air Products is committed to the initiative of the Chemical Manufacturers Association (CMA) known as Responsible Care. This initiative focuses on the safe manufacturing, distribution, use, recycling, and disposal of chemicals. Proper communication through accurate shipping descriptions and full disclosure of hazard information in the MSDS plays a key role in fulfilling obligations under Responsible Care. Maintaining shipping descriptions and MSDSs requires a major effort. Most corporate systems are intensely manual.
Case-Based Reasoning: A Research Paradigm
"I have but one lamp by which my feet are guided, and that is the lamp of experience. I know no way of judging of the future but by the past." AI researchers seek to understand the nature of intelligence and human thought. They examine a range of human cognitive behavior, including memory, learning, planning, and problem solving and look for principles that play general descriptive and explanatory roles. The second agenda for AI research is technological.
Case-and Constraint-Based Project Planning for Apartment Construction
To effectively generate a fast and consistent apartment construction project network, Hyundai Engineering and Construction and Korea Advanced Institute of Science and Technology developed a case-and constraint-based project-planning expert system for an apartment domain. The reason we chose the case-and constraintbased approach is intuitive. Second, during system development, crosschecking of cases with constraints improves the quality of both of them. Through the crosschecking process, the system developers can refine the previous cases to the high-quality referential cases and simultaneously validate and verify the domain constraints. In the area of project management, there has been a lot of research and development of network-based project-planning methods and management techniques, assuming that a project network is given to the project manager (Bent and Thumann 1994).
A Case-Based Rangeland Management Adviser
Figure 1 illustrates grasshopper infestation densities in the western United States during 2000, a fairly typical year. In years of heavy infestation, grasshopper densities and economic losses might be much higher. For example, during the 1986 to 1987 outbreak, over 20 million acres of rangeland were treated for grasshoppers in the western United States at a cost of more than $75 million. In Wyoming, the estimated total annual loss to grasshoppers is roughly $19 million. The southeastern quadrant of the state is particularly prone to grasshopper infestations, with significant areas of high-grasshopper densities in 30 of the last 34 years.
The AI research group in the AI research spectrum, including
Kolodner has long been investigating the use of case-based reasoning for solving a range of complex problems in a variety of domains. Goel is exploring the integration of different types of knowledge and methods of reasoning for planning and design problem solving. In case-based reasoning (Kolodner 1990), a reasoner solves new problems by remembering previous situations similar to the new situation.