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Representing and Reasoning about Dynamic Multi-Agent Domains: An Action Language Approach

Abstract Reasoning about actions forms the basis of many tasks such as prediction, planning, and diagnosis in a dynamic domain. Within the reasoning about actions community, a broad class of languages, called action languages, has been developed together with a methodology for their use in representing and reasoning about dynamic domains. With a few notable exceptions, the focus of these efforts has largely centered around single-agent systems. Agents rarely operate in a vacuum however, and almost in parallel, substantial work has been done within the dynamic epistemic logic community towards understanding how the actions of an agent may effect not just his own knowledge and/or beliefs, but those of his fellow agents as well. What is less understood... (more)
Created Date 2018
Contributor Gelfond, Gregory (Author) / Baral, Chitta (Advisor) / Kambhampati, Subbarao (Committee member) / Lee, Joohyung (Committee member) / Moss, Larry (Committee member) / Cao Son, Tran (Committee member) / Arizona State University (Publisher)
Subject Computer science / Artificial intelligence / Logic / Action Languages / Answer Set Programming / Artificial Intelligence / Knowledge Representation / Modal Logic / Multi-Agent Systems
Type Doctoral Dissertation
Extent 168 pages
Language English
Reuse Permissions All Rights Reserved
Note Doctoral Dissertation Computer Science 2018
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis