RankPL: A Qualitative Probabilistic Programming Language

被引：2

作者：

Rienstra, Tjitze ^{[1
]}

机构：

[1] Univ Luxembourg, Comp Sci & Commun, Luxembourg, Luxembourg

来源：

SYMBOLIC AND QUANTITATIVE APPROACHES TO REASONING WITH UNCERTAINTY, ECSQARU 2017 | 2017年 / 10369卷

关键词：

D O I：

10.1007/978-3-319-61581-3_42

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we introduce RankPL, a modeling language that can be thought of as a qualitative variant of a probabilistic programming language with a semantics based on Spohn's ranking theory. Broadly speaking, RankPL can be used to represent and reason about processes that exhibit uncertainty expressible by distinguishing "normal" from "surprising" events. RankPL allows (iterated) revision of rankings over alternative program states and supports various types of reasoning, including abduction and causal inference. We present the language, its denotational semantics, and a number of practical examples. We also discuss an implementation of RankPL that is available for download.

引用

页码：470 / 479

页数：10

共 11 条

[1]

[Anonymous], 2014, CORR

[2]

[Anonymous], 1990, P 3 C THEORETICAL AS

[3]

[Anonymous], 2008, P 24 C UNC ART INT

[4]

[Anonymous], 1995, Handbook of Logic in Artificial Intelligence and Logic Programming

[5] On the logic of iterated belief revision [J].

Darwiche, A ;

Pearl, J .

ARTIFICIAL INTELLIGENCE, 1997, 89 (1-2) :1-29

[6] Qualitative probabilities for default reasoning, belief revision, and causal modeling [J].

Goldszmidt, M ;

Pearl, J .

ARTIFICIAL INTELLIGENCE, 1996, 84 (1-2) :57-112

[7]

Halpern Joseph Y., 2005, Reasoning About Uncertainty

[8] SEMANTICS OF PROBABILISTIC PROGRAMS [J].

KOZEN, D .

JOURNAL OF COMPUTER AND SYSTEM SCIENCES, 1981, 22 (03) :328-350

[9]

Kyburg Jr H.E, 1961, PROBABILITY LOGIC RA

[10]

Pfeffer A., 2009, 137 CHARL RIV AN

← 1 2 →