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Abstract
A notion of probabilistic lambdacalculus usually comes with a prescribed reduction strategy, typically callbyname or callbyvalue, as the calculus is nonconfluent and these strategies yield different results. This is a break with one of the main advantages of lambdacalculus: confluence, which means results are independent from the choice of strategy. We present a probabilistic lambdacalculus where the probabilistic operator is decomposed into two syntactic constructs: a generator, which represents a probabilistic event; and a consumer, which acts on the term depending on a given event. The resulting calculus, the Probabilistic Event LambdaCalculus, is confluent, and interprets the callbyname and callbyvalue strategies through different interpretations of the probabilistic operator into our generator and consumer constructs. We present two notions of reduction, one via finegrained local rewrite steps, and one by generation and consumption of probabilistic events. Simple types for the calculus are essentially standard, and they convey strong normalization. We demonstrate how we can encode callbyname and callbyvalue probabilistic evaluation.
Original language  English 

Pages  136156 
Number of pages  21 
DOIs  
Publication status  Published  1 Jan 2020 
Event  23rd International Conference on Foundations of Software Science and Computation Structures  Dublin, Ireland Duration: 25 Apr 2020 → … https://etaps.org/2020/fossacs 
Conference
Conference  23rd International Conference on Foundations of Software Science and Computation Structures 

Abbreviated title  FoSSaCS 2020 
Country  Ireland 
City  Dublin 
Period  25/04/20 → … 
Internet address 
ASJC Scopus subject areas
 Theoretical Computer Science
 Computer Science(all)
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Projects
 1 Active

Typed LambdaCalculi with Sharing and Unsharing
Engineering and Physical Sciences Research Council
1/01/19 → 31/12/21
Project: Research council