MASSPEC: multiagent system specification through policy exploration and checking

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dc.contributor.author Harmon, Scott J.
dc.date.accessioned 2012-04-24T19:34:39Z
dc.date.available 2012-04-24T19:34:39Z
dc.date.issued 2012-04-24
dc.identifier.uri http://hdl.handle.net/2097/13635
dc.description.abstract Multiagent systems have been proposed as a way to create reliable, adaptable, and efficient systems. As these systems grow in complexity, configuration, tuning, and design of these systems can become as complex as the problems they claim to solve. As researchers in multiagent systems engineering, we must create the next generation of theories and tools to help tame this growing complexity and take some of the burden off the systems engineer. In this thesis, I propose guidance policies as a way to do just that. I also give a framework for multiagent system design, using the concept of guidance policies to automatically generate a set of constraints based on a set of multiagent system models as well as provide an implementation for generating code that will conform to these constraints. Presenting a formal definition for guidance policies, I show how they can be used in a machine learning context to improve performance of a system and avoid failures. I also give a practical demonstration of converting abstract requirements to concrete system requirements (with respect to a given set of design models). en_US
dc.description.sponsorship Air Force Office of Scientific Research en_US
dc.language.iso en_US en_US
dc.publisher Kansas State University en
dc.subject Multiagent Systems en_US
dc.subject Policies en_US
dc.subject Artificial Intelligence en_US
dc.subject Model Checking en_US
dc.subject Software Engineering en_US
dc.title MASSPEC: multiagent system specification through policy exploration and checking en_US
dc.type Dissertation en_US
dc.description.degree Doctor of Philosophy en_US
dc.description.level Doctoral en_US
dc.description.department Department of Computing and Information Sciences en_US
dc.description.advisor Scott A. DeLoach en_US
dc.subject.umi Artificial Intelligence (0800) en_US
dc.subject.umi Computer Science (0984) en_US
dc.subject.umi Engineering (0537) en_US
dc.date.published 2012 en_US
dc.date.graduationmonth May en_US


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