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Heuristic Search For Physics-Based Problems: Angry Birds in PDDL+
This paper studies how a domain-independent planner and combinatorial search can be employed to play Angry Birds, a well established AI challenge problem.
Learning to Operate in Open Worlds by Adapting Planning Models
Planning agents are ill-equipped to act in novel situations in which their domain model no longer accurately represents the world.
Review of Algorithms for Compressive Sensing of Images
We provide a comprehensive review of classical algorithms for compressive sensing of images, focused on Total variation methods, with a view to application in LiDAR systems.
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