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arXiv 1306.3548cs.AI

Encoding Higher Level Extensions of Petri Nets in Answer Set Programming

Arizona State University(亚利桑那州立大学);National Institute of Informatics(国立信息学研究所)

Saadat Anwar, Chitta Baral, Katsumi Inoue

英文摘要:

Answering realistic questions about biological systems and pathways similar to the ones used by text books to test understanding of students about biological systems is one of our long term research goals. Often these questions require simulation based reasoning. To answer such questions, we need formalisms to build pathway models, add extensions, simulate, and reason with them. We chose Petri Nets and Answer Set Programming (ASP) as suitable formalisms, since Petri Net models are similar to biological pathway diagrams; and ASP provides easy extension and strong reasoning abilities. We found that certain aspects of biological pathways, such as locations and substance types, cannot be represented succinctly using regular Petri Nets. As a result, we need higher level constructs like colored tokens. In this paper, we show how Petri Nets with colored tokens can be encoded in ASP in an intuitive manner, how additional Petri Net extensions can be added by making small code changes, and how this work furthers our long term research goals. Our approach can be adapted to other domains with similar modeling needs.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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