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Full-Text Articles in Engineering
Science And Engineering In Knowledge Representation And Reasoning, Lynn Stein
Science And Engineering In Knowledge Representation And Reasoning, Lynn Stein
Lynn Andrea Stein
As a field, knowledge representation has often been accused of being off in a theoretical no-man's land, removed from, and largely unrelated to, the central issues in AI. This article argues that recent trends in KR instead demonstrate the benefits of the interplay between science and engineering, a lesson from which all AI could benefit. This article grew out of a survey talk on the Third International Conference on Knowledge Representation and Reasoning (KR-92) (Nebel, Rich, and Swartout 1992) that I presented at the Thirteenth International Joint Conference on Artificial Intelligence (IJCAI-93).
Rethinking Cs101: Or, How Robots Revolutionize Introductory Computer Programming, Lynn Stein
Rethinking Cs101: Or, How Robots Revolutionize Introductory Computer Programming, Lynn Stein
Lynn Andrea Stein
Introductory computer science education is entrenched in an outdated computational model. Although it corresponds neither to our computing environments nor to our work, we insist on teaching our introductory students computation-as-calculation, a mathematical problem-solving view of the role of the computer program. We can dramatically improve this situation -- and, as a corollary, all of undergraduate computer science -- by focusing on the kind of dynamic, interactive, inherently parallel computation that occurs in spreadsheets and video games, web applications and robots.
Building Brains For Bodies, Lynn Stein, Rodney Brooks
Building Brains For Bodies, Lynn Stein, Rodney Brooks
Lynn Andrea Stein
We describe a project to capitalize on newly available levels of computational resources in order to understand human cognition. We are building an integrated physical system including vision, sound input and output, and dextrous manipulation, all controlled by a continuously operating large scale parallel MIMD computer. The resulting system will learn to "think" by building on its bodily experiences to accomplish progressively more abstract tasks. Past experience suggests that in attempting to build such an integrated system we will have to fundamentally change the way artificial intelligence, cognitive science, linguistics, and philosophy think about the organization ofintelligence. We expect to …
Skeptical Inheritance: Computing The Intersection Of Credulous Extensions, Lynn Stein
Skeptical Inheritance: Computing The Intersection Of Credulous Extensions, Lynn Stein
Lynn Andrea Stein
Ideally skeptical inheritance supports exactly those inferences true in every credulous extension of an inheritance hierarchy. We provide a formal definition of ideally skeptical inheritance. We show that two path-based approaches fail to capture ideally skeptical inheritance, and that there are inheritance hierarchies for which there are more always-true inferences than always-supported paths. We describe an ATMS-like scheme that computes ideally skeptical inheritance and represents hierarchical dependencies using a limited form of Boolean satisfiability. Finally, we demonstrate a preemption (specificity) strategy for which ideally skeptical inheritance is polynomial time computable.