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An Investigation of Topics in Model-Lite Planning and Multi-Agent Planning


Abstract Automated planning addresses the problem of generating a sequence of actions that enable a set of agents to achieve their goals.This work investigates two important topics from the field of automated planning, namely model-lite planning and multi-agent planning. For model-lite planning, I focus on a prominent model named Annotated PDDL and it's related application of robust planning. For this model, I try to identify a method of leveraging additional domain information (available in the form of successful plan traces). I use this information to refine the set of possible domains to generate more robust plans (as compared to the original planner) for any given problem. This method also provides us a way of overcoming one of the major dra... (more)
Created Date 2016
Contributor Sreedharan, Sarath (Author) / Kambhampati, Subbarao (Advisor) / Zhang, Yu (Advisor) / Ben Amor, Heni (Committee member) / Arizona State University (Publisher)
Subject Artificial intelligence / Automated planning
Type Masters Thesis
Extent 83 pages
Language English
Copyright
Reuse Permissions All Rights Reserved
Note Masters Thesis Computer Science 2016
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis