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It is well known that (discrete) probability distributions can be implemented as monads in Haskell in various more or less sophisticated ways.
Things become more complicated when you consider processes that can take a probabilistic amount of time or even fail with a certain probability. How do such processes compose sequentially or in parallel?
An example of this is sending a message in a network. Transmission time follows a (continuous) probability distribution, and it is even possible that the message will never reach its receiver.
In this presentation, Lars will extend the standard notion of probability monad to include a notion of probabilistic duration, which will enable you to model things like communication in a network of nodes. Lars will answer questions like: "How long will it take a signal to reach each node in the network?" and "How does the answer depend on network topology?"
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