This work analyzes the central role of interpretation in non-routine design. Based on this analysis, a theory of computer support for interpretation in cooperative design is constructed. The theory is grounded in studies of design and interpretation. It is illustrated by mechanisms provided by a software substrate for computer-based design environments, applied to a sample task of lunar habitat design. Computer support of

In its early stages, the field of artificial intelligence (AI) had as its main goal the invention of computer programs having the general problem solving abilities of humans. Along the way, there developed a major shift of emphasis from general-purpose programs toward "performance programs"---ones whose competence was highly specialized and limited to particular areas of expertise. In this paper I claim that AI is now at the beginning of another transition---one that will re-invigorate efforts to build programs of general, human-like competence. These programs will use specialized performance programs as tools, much like humans do. Keywords: autonomous agents, general problem solving, habile systems Copyright c fl1995 Nils J. Nilsson [This paper is being submitted to the AI Magazine.] 1 Diversions from the Main Goal Over forty years ago, soon after the birth of electronic computers, people began to think that human levels of intelligence might someday be realized in computer program...

This research monograph examines the potential of constructivist learning environments for developing prerequisites of expert knowledge during university studies. Drawing on recent theories of the development of expert knowledge and on the constructivist view of learning, an experiment was conducted in an educational psychology course. The primary purpose of the study was to compare the learning outcomes of students who studied the course material in a constructivist learning environment with those of students who learned it under traditional teaching and studying conditions. Students in the constructivist learning environment acquired more diversi"ed knowledge. In addition, a theory will be presented about what actually changes when conceptual change occurs. # 1999 Elsevier Science Ltd. All rights reserved.

George Santayana's statement, "Those who cannot remember the past are condemned to repeat it, " is only half true. The past also includes successful histories. If you haven't been made aware of them, you're often condemned not to repeat their successes. In a rapidly expanding field such as software engineering, this happens a lot. Extensive studies of many software projects such as the Standish Reports offer convincing evidence that many projects fail to repeat past successes. This paper tries to identify at least some of the major past software experiences that were well worth repeating, and some that were not. It also tries to identify underlying phenomena influencing the evolution of software engineering practices that have at least helped the author appreciate how our field has gotten to where it has been and where it is. A counterpart Santayana-like statement about the past and future might say, "In an era of rapid change, those who repeat the past are condemned to a bleak future. " (Think about the dinosaurs, and think carefully about software engineering maturity models that emphasize repeatability.) This paper also tries to identify some of the major sources of change that will affect software engineering practices in the next couple of decades, and identifies some strategies for assessing and adapting to these sources of change. It also makes some first steps towards distinguishing relatively timeless software engineering principles that are risky not to repeat, and conditions of change under which aging practices will become increasingly risky to repeat.

We propose certain non-Turing models of computation, but our intent is not to advocate models that surpass the power of Turing Machines (TMs), but to defend the need for models with orthogonal notions of power. We review the nature of models and argue that they are relative to a domain of application and are ill-suited to use outside that domain. Hence we review the presuppositions and context of the TM model and show that it is unsuited to natural computation (computation occurring in or inspired by nature). Therefore we must consider an expanded definition of computation that includes alternative (especially analog) models as well as the TM. Finally we present an alternative model, of continuous computation, more suited to natural computation. We conclude with remarks on the expressivity of formal mathematics. Key words: analog computation, analog computer, biocomputation, computability, computation on reals, continuous computation, formal system, hypercomputation,

In this article I argue that the organizational involvement of large scale information technology packages, such as those known as Enterprise Resource Planning (ERP), has important implications that go far beyond the acknowledged effects of keeping the organizational operations accountable and integrated across functions and production sites. My claim is that ERP packages are predicated upon an understanding of human agency as a procedural affair and of organizations as an extended series of functional or cross-functional transactions. Accordingly, the massive introduction of ERP packages to organizations is bound to have serious implications that precisely recount the procedural forms by which such packages instrument organizational operations and fashion organizational roles. The conception of human agency and organizational operations in procedural terms may seem reasonable yet it recounts a very specific and, in a sense, limited understanding of humans and organizations. The distinctive status of framing human agency and organizations in procedural terms becomes evident in its juxtaposition with other forms of human action like improvisation, exploration or playing. These latter forms of human involvement stand out against the serial fragmentation underlying procedural action. They imply acting upon the world on loose premises that trade off a variety of forms of knowledge and courses of action in attempts to explore and discover alternative ways of coping with reality. Key Words: Human agency, behaviour, information infrastructures, integration, organizational action, procedural action, procedural knowledge, standardization

The paper describes a connectionist model that deals with the inheritance problem in an efficient and natural way. Based on the connectionist architecture CONSYDERR, we analyze the problem of property inheritance and formulate it in ways facilitating conceptual clarity and connectionist implementation. A set of "benchmarks" is specified for ensuring the correctness of solution mechanisms; parameters of CONSYDERR are formally derived to satisfy these benchmark requirements. The paper also discusses how chaining of is-a links and multiple inheritance can be handled in this architecture. This paper shows that CONSYDERR with a two-level dual (localist and distributed) representation can handle inheritance and cancellation of inheritance correctly and extremely efficiently, in constant time instead of proportional to the length of a chain in an inheritance hierarchy. It also demonstrates the utility of a meaning-oriented intensional approach (with features), for supplementing a...

INTRODUCTION How does an autonomous agent that interacts with an environment learn to survive in the environment and make the most out of it? More specifically, how can it develop a set of coping skills that are highly specific (geared toward very particular situations) and thus highly efficient but, at the same time, acquire sufficiently general knowledge that can be readily applied to a variety of different situations? Although humans seem to possess such abilities and seem to be able to achieve an appropriate balance between the two sides, existing AI systems fall far short. There has been a great deal of work demonstrating the difference between procedural knowledge and declarative knowledge (or conceptual and subconceptual knowledge; e.g., Anderson 1982, 1990, Keil 1989, Damasio et al. 1990, Sun 1994). It is believed that a balance of the two is essential to the development of complex cognitive agents. For example, one way to learn a sequential decision task, such as navi

this paper begins to address.

Reviews of the state of the professional practice in Requirements Engineering (RE) stress that the RE process is both complex and hard to describe, and suggest there is a significant difference between competent and "approved " practice. "Approved" practice is reflected by (in all likelihood, in fact, has its genesis in) RE education, so that the knowledge and skills taught to students do not match the knowledge and skills required and applied by competent practitioners. A recent action research study describes a new understanding of the RE process. RE is revealed as inherently creative, involving cycles of building and major reconstruction of the models developed,