30,959 research outputs found
Abstracting Noisy Robot Programs
Abstraction is a commonly used process to represent some low-level system by
a more coarse specification with the goal to omit unnecessary details while
preserving important aspects. While recent work on abstraction in the situation
calculus has focused on non-probabilistic domains, we describe an approach to
abstraction of probabilistic and dynamic systems. Based on a variant of the
situation calculus with probabilistic belief, we define a notion of
bisimulation that allows to abstract a detailed probabilistic basic action
theory with noisy actuators and sensors by a possibly deterministic basic
action theory. By doing so, we obtain abstract Golog programs that omit
unnecessary details and which can be translated back to a detailed program for
actual execution. This simplifies the implementation of noisy robot programs,
opens up the possibility of using deterministic reasoning methods (e.g.,
planning) on probabilistic problems, and provides domain descriptions that are
more easily understandable and explainable
Probabilistic foundations of quantum mechanics and quantum information
We discuss foundation of quantum mechanics (interpretations, superposition,
principle of complementarity, locality, hidden variables) and quantum
information theory.Comment: Contextual probabilistic viewpoint to quantum cryptography projec
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