Intelligence in scientific computing

Abelson, Harold; Eisenberg, Michael; Halfant, Matthew; Katzenelson, Jacob; Sacks, Elisha; Sussman, Gerald Jay; Wisdom, Jack; Yip, Ken

doi:10.1145/63485.63486

Cited by 84 publications

(11 citation statements)

References 14 publications

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“…Пространственная агрегация мотивирована некоторыми проблемами пространственного рассуждения, поднятыми Абельсоном и др. (Abelson et al, 1989). В статье Абельсона описывается ряд подходов к интерпретации численных результатов моделирования динамических систем.…”

Section: результаты исследования качественные рассужденияunclassified

Qualitative Spatial Reasoning and Spatial Relations

2017

European Journal of Psychological Studies

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The article describes the relationship between spatial reasoning and a series of spatial models, the most important of which are spatial relationships. Paper reveals the content of qualitative reasoning. Paper reveals the content of qualitative spatial reasoning. The article offers new concepts in the field of qualitative spatial reasoning. Paper reveals these new concepts: information units, spatial relationships, information structures and information situations. The article shows that information units are the basis of reasoning, information constructions by the mechanism of spatial conclusions. The article proves that spatial relations form the basis of qualitative analysis and qualitative spatial reasoning.

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Section: результаты исследования качественные рассужденияunclassified

Qualitative Spatial Reasoning and Spatial Relations

2017

European Journal of Psychological Studies

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“…Abelson et al, 1989;Zhao, 1974;Bradley, 1992). Broadly speaking, the purpose of this research is to design computational systems that can assist the working scientist by (e.g.)…”

Section: Craft Advisorsmentioning

confidence: 99%

Shop Class for the Next Millenium: Education through Computer-Enriched Handicrafts

Eisenberg¹,

Eisenberg

1998

JIME

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Abstract:In this paper we use our experiences with the HyperGami program as a springboard for a broader look at the future of computationally-enriched handicrafts. HyperGami is an educational application for the design and construction of mathematical models and sculptures in paper; as such, it serves as a source of examples and insights for the more general problem of how to integrate the "high-tech" features of computation with the "low-tech" features of traditional craft materials in education. We begin by describing the HyperGami program, focusing on those features that were designed in response to problems encountered by papercrafters; we illustrate the program's capabilities by presenting some of our own and our students' papercraft designs; and we describe our initial steps in implementing elements of HyperGami on the World Wide Web. In the closing sections of the paper, we explore the broader educational issues involved in integrating computation and handicrafts; and we conclude with a discussion of how physical objects could play a role in a future "educational object economy."

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“…Aside from work on visualization, our work on SIGMA bears a close relationship to the growing body of work on applying knowledge-based techniques to various aspects of scientific and engineering computation (Abelson, Eisenberg, Halfant, Katzenelson, Sacks, Sussman, et al, 1989;Barstow, 1985;Cook, 1990;Ford & Chatelin, 1987;Kook & Novak, 1991;Palmer & Cremer, 1991;Robertson, Bundy, Uschold, & Muetzelfeldt, 1989;Weld & deKleer, 1990). We review some of the particularly relevant systems for comparison below.…”

Section: Related Workmentioning

confidence: 99%

A knowledge-based prototyping environment for construction of scientific modeling software

1994

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Over the past 30 years, scientific software models have played an increasingly prominent role in the conduct of science. Unfortunately, scientific models can be difficult and time-consuming to implement, and there is little software engineering support specifically available for constructing scientific models. Because these models are not easily specified to scientifically-naive programmers, and because the scientist requires intimate knowledge of the code to conduct experiments, many scientists implement their own models. This coding activity takes valuable time away from their primary scientific mission.We have developed a knowledge-based software development tool that assists scientists in prototyping scientific models. With a specialized graphical user interface, the scientist constructs a high-level visual specification that captures the essential computational dependencies in the desired model. The system uses its scientific domain knowledge to ensure that the model being built is consistent and coherent. The final product is an executable prototype of a scientific model. Our tool accelerates the model-building process and eliminates the scientist's need to program in a formal language. Furthermore, the models developed with this tool are easier to understand and reuse than typical low-level scientific modeling code. At present, models developed with our system are restricted to those involving non-coupled algebraic and first order ordinary differential equations. Research is ongoing to lessen this restriction and support models with simultaneous equations.

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Intelligence in scientific computing

Cited by 84 publications

References 14 publications

Qualitative Spatial Reasoning and Spatial Relations

Qualitative Spatial Reasoning and Spatial Relations

Shop Class for the Next Millenium: Education through Computer-Enriched Handicrafts

A knowledge-based prototyping environment for construction of scientific modeling software

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