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Semantics of the probabilistic typed...

Draheim, Dirk.

Semantics of the probabilistic typed lambda calculusMarkov chain semantics, termination behavior, and denotational semantics /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Semantics of the probabilistic typed lambda calculusby Dirk Draheim.
其他題名:	Markov chain semantics, termination behavior, and denotational semantics /
作者:	Draheim, Dirk.
出版者:	Berlin, Heidelberg :Springer Berlin Heidelberg :2017.
面頁冊數:	viii, 218 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Lambda calculus.
電子資源:	http://dx.doi.org/10.1007/978-3-642-55198-7
ISBN:	9783642551987$q(electronic bk.)

Semantics of the probabilistic typed lambda calculusMarkov chain semantics, termination behavior, and denotational semantics /
Draheim, Dirk.

Semantics of the probabilistic typed lambda calculusMarkov chain semantics, termination behavior, and denotational semantics /[electronic resource] :by Dirk Draheim. - Berlin, Heidelberg :Springer Berlin Heidelberg :2017. - viii, 218 p. :ill., digital ;24 cm.

Part I: The Probabilistic Lambda-Calculus and its Semantics -- Introduction -- Syntax and Operational Semantics -- The Working Probabilistic Lambda Calculus -- Properties of the Markov Chain Semantics -- Denotational Semantics -- Semantical Correspondences -- Categorical Treatment -- Probabilism and Non-Determinism -- Part II: Natural Probabilistic Reasoning -- On Natural Two-Tier Semantics for Propositional Logics -- Natural Semantics of Propositions -- Finite Discrete Stochastics Reconsidered -- Lambda-Calculus Definitions -- Markov Chains -- Basic Logic Language and Semantics Definitions -- References -- Index.

This book takes a foundational approach to the semantics of probabilistic programming. It elaborates a rigorous Markov chain semantics for the probabilistic typed lambda calculus, which is the typed lambda calculus with recursion plus probabilistic choice. The book starts with a recapitulation of the basic mathematical tools needed throughout the book, in particular Markov chains, graph theory and domain theory, and also explores the topic of inductive definitions. It then defines the syntax and establishes the Markov chain semantics of the probabilistic lambda calculus and, furthermore, both a graph and a tree semantics. Based on that, it investigates the termination behavior of probabilistic programs. It introduces the notions of termination degree, bounded termination and path stoppability and investigates their mutual relationships. Lastly, it defines a denotational semantics of the probabilistic lambda calculus, based on continuous functions over probability distributions as domains. The work mostly appeals to researchers in theoretical computer science focusing on probabilistic programming, randomized algorithms, or programming language theory.

ISBN: 9783642551987$q(electronic bk.)

Standard No.: 10.1007/978-3-642-55198-7doiSubjects--Topical Terms:

277880
Lambda calculus.

LC Class. No.: QA9.5

Dewey Class. No.: 511.35

Semantics of the probabilistic typed lambda calculusMarkov chain semantics, termination behavior, and denotational semantics /
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520 $a This book takes a foundational approach to the semantics of probabilistic programming. It elaborates a rigorous Markov chain semantics for the probabilistic typed lambda calculus, which is the typed lambda calculus with recursion plus probabilistic choice. The book starts with a recapitulation of the basic mathematical tools needed throughout the book, in particular Markov chains, graph theory and domain theory, and also explores the topic of inductive definitions. It then defines the syntax and establishes the Markov chain semantics of the probabilistic lambda calculus and, furthermore, both a graph and a tree semantics. Based on that, it investigates the termination behavior of probabilistic programs. It introduces the notions of termination degree, bounded termination and path stoppability and investigates their mutual relationships. Lastly, it defines a denotational semantics of the probabilistic lambda calculus, based on continuous functions over probability distributions as domains. The work mostly appeals to researchers in theoretical computer science focusing on probabilistic programming, randomized algorithms, or programming language theory.
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