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by Sungwoo Park, Frank Pfenning, Sebastian Thrun
In Proceedings of the 2003 ACM SIGPLAN international workshop on Types in languages design and implementation
http://www-2.cs.cmu.edu/~fp/papers/prob03.ps
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Abstract:
Motivated by many practical applications that have to compute in the presence of uncertainty, we propose a monadic probabilistic language based upon the mathematical notion of sampling function. Our language provides a unified representation scheme for probability distributions, enjoys rich expressiveness, and o#ers high versatility in encoding probability distributions. We also develop a novel style of operational semantics called a horizontal operational semantics, under which an evaluation returns not a single outcome but multiple outcomes. We have preliminary evidence that the horizontal operational semantics improves the ordinary operational semantics with respect to both execution time and accuracy in representing probability distributions. Categories and Subject Descriptors
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