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).
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- Partial requirement for: M.S., Arizona State University, 2016Note typethesis
- Includes bibliographical references (pages 71-72)Note typebibliography
- Field of study: Computer science