An important aspect of any interactive computer system is its ease of use. On-line assistance is a major contributor to software usability. Conventional on-line assistance includes on-line documentation, or keyword access to textual help descriptions. More sophisticated on-line assistance includes intelligent help which provides immediate assistance for a specific problem, and intelligent training whose main goal is to support the user in learning about the system. These contemporary forms of intelligent assistance represent knowledge about the particular application, the user and the particular tasks the user is to perform. In addition, they possess inferencing capabilities to model the individual user's goals, plans, intentions and knowledge. This paper provides an overview of on-line assistance research, from empirical studies that attempt to determine the nature of effective assistance, to the design of intelligent on-line assistance systems capable of tailoring the assistance to the individual user. For readers interested in more details, recommendations for further reading in the related areas of advice-giving and intelligent help, intelligent user interfaces, critiquing, intelligent tutoring systems, and on-line documentation and hypertext are given.

Finance is a challenging yet appropriate domain for model-based reasoning, an area of research otherwise grounded in classical physics. Among the many features that suggest a model-based approach are that firms have formal internal structures, business entities have idealizable behaviours, and there is a history of formal analysis of business problems. This article discusses the motivations and foundations of the model-based approach, and surveys several existing artificial intelligence programs that exploit its advantages. The survey shows that there are ample opportunities for useful systems and significant research in this area. However, accomplishing either of these goals depends crucially upon moving beyond qualitative models based only on accounting information, which tend not to capture the actual complexities of the domain.

Designing is a skill central to many human tasks. Designers are constantly producing newer and better artifacts, generating innovative solutions to problems in our world. This article looks at innovation and research that is aimed at developing theories and methodologies for innovative design. We view design as a process of association and exploration. These two approaches are fundamental to innovation. The aim of exploration is to generate a large variety of design alternatives by breaking away from the norms, by looking in unlikely places, and by relaxing binding constraints. Exploration exposes possibilities that would not normally have been considered, possibilities that may serendipitously lead to innovative solutions. Association, on the other hand, attempts to exploit previous design experiences in a new design context. This is done by recognizing useful analogies that can help in synthesizing parts of a design, recognizing unforeseen problems, and discovering opportunities. This article is the second part of a two-part paper that presents and discusses a variety of association and exploration methods. This part examines exploration techniques, some of which have been used in actual design systems, and others that point to the solution of some open questions in design research. We develop these ideas by examining connections between design research and other disciplines such as artificial intelligence, evolutionary epistemology, and the automated discovery literature.

Many benefits potentially stem from a structured representation and use of “design rationales”, i.e. the deliberations underlying a software design process. Explicitly-represented rationales help us understand the design better so that we can produce a better design, maintain the resulting artifact better, and exploit the cumulated knowledge when we need to redesign it. Explicit representation of the rationales also provide a basis for reviewing or justifying the decisions that have been made, for communicating with other members of the design team more easily, and for defining computer services that support various design activities, such as keeping track of dependencies or managing multiple viewpoints. Technologies, that have recently become available, such as multi-media and distributed databases, provide the necessary ingredients for pursuing these potential benefits seriously. As a result, in the past few year we have seen growing interest in design rationale management.

The 7th Annual Knowledge-Based Software Engineering Conference was held at the McLean Hilton at Tysons Comer, in McLean, Virginia, on Sept. 20–23, 1992. This conference was sponsored by Rome Laboratory and held in cooperation with the IEEE Computer Society, ACM SIGART and SIGSOFT, and the American Association for Artificial Intelligence (AAAI).