J. Scott Penberthy

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we present ZENO, a least commitment planner that handles actions occurring over extended intervals of time. Deadline goals, metric preconditions, metric effects, and continuous change are supported. Simultaneous actions are alIowed when their effects do not interfere. Unlike most planners that deal with complex languages, the ZENO planning algorithm is(More)
Addanki, S., R. Cremonini and J.S. Penberthy, Graphs of models, Artificial Intelligence 51 (1991) 145-177. Solving analysis problems in physical worlds requires the representation of large amounts of knowledge. Recently, there has been much interest in using multiple models, in the engineering sense of the word, to capture the complex and diverse knowledge(More)
Solving design and analysis problems in physical worlds requires the representation of large amounts of knowledge. Recently, there has been much interest in expl ic i t ly making assumptions to decompose this knowledge in to smaller Models. A crucial aspect of problemsolving paradigms based on models is that they include methods to automat ica l ly , and(More)
BACKGROUND Argon plasma coagulation (APC) has been used to trim uncovered Elgiloy stents, but the extent of thermal damage and bile duct injury is not known. The goal of this study was to evaluate the safety and efficacy of APC for this application. METHODS Eight Elgiloy (covered and uncovered) and four nitinol stents were deployed in the bile duct at(More)
We present ZENO, an implemented, partialorder planner that handles simultaneous actions occurring over extended time intervals. The action language supports a large subset of KRSL, including metric constraints, deadline goals, and synergistic (additive) effects. We believe the algorithm is both sound and complete. The chief technical contributions are (1)(More)
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