课题基金 / 基金详情

RI: Small: Automated Optimization of Programs and Processing Tools in Answer Set Programming

RI: Small: Automated Optimization of Programs and Processing Tools in Answer Set Programming
RI:小:答案集编程中程序和处理工具的自动优化
批准号:
1707371
负责人:
Yuliya Lierler
金额:
$49.95万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-01 至 2022-08-31

项目摘要

项目成果

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中文摘要
翻译
答案集编程(ASP)是一种知识表示和声明性约束编程的形式,用于表示和解决约束满足问题。ASP的根源在于需要支持为复杂的知识密集型应用程序快速设计健壮且可靠的软件解决方案。它提供了一种高级编程范例,用于将应用程序领域建模为逻辑语言中的理论,并将所有计算问题留给自动推理。ASP已被用于各种科学和工业应用,包括产品配置、决策支持系统和修复大型生物网络。该项目旨在改进ASP问题的特定编码,以及底层自动推理或求解器的性能。该项目侧重于三个相关的研究重点,每个重点都利用了ASP的高级问题描述。1)对程序重写的研究将为给定的问题产生可替代的编码;2)求解器组合的发展将提高整体推理性能,并通过ASP域编码的替代求解器的可用性提供鲁棒性;3)将研究参数调整以提高单个求解器的性能。该项目将建立一个评估平台,系统地实施和验证这些研究活动。该评估平台将由实验编码和约束满足和逻辑规划技术的基准问题集合以及相关的求解器竞赛组成。
英文摘要
Answer Set Programming (ASP) is a form of knowledge representation and declarative constraint programming used to represent and solve constraint satisfaction problems. ASP has its roots in the need to support fast design of robust and reliable software solutions for complex knowledge-intensive applications. It provides a high-level programming paradigm for modeling an application domain as a theory in a language of logic, and leaves all computational concerns to automated reasoning. ASP has been used in a variety of scientific and industrial applications, including product configuration, decision support systems, and repairing large-scale biological networks. This project aims to improve both the specific encoding of the ASP problems, and the performance of the underlying automated reasoner or solver. The project focuses on three related research thrusts, each of which leverages the high-level problem description of ASP. 1) Research in program rewriting will generate alternative encodings for a given problem; 2) the development of solver portfolios will improve overall reasoning performance and provide robustness through availability of alternate solvers for the ASP domain encodings; and 3) parameter tuning will be investigated to improve the performance of individual solvers. The project will establish an evaluation platform to systematically implement and validate each of these research activities. This evaluation platform will be comprised of both experiment encodings and a collection of benchmark problems from techniques in constraint satisfaction and logic programming as well as related solver competitions.
期刊论文(20)
专著(0)
科研奖励(0)
会议论文
Automated Aggregator - Rewriting with the Counting Aggregate
自动聚合器 - 用计数聚合重写
DOI: 10.4204/eptcs.325.17
发表时间: 2020
期刊: Electronic Proceedings in Theoretical Computer Science
影响因子: --
作者: [Dingess, Michael, Truszczynski, Miroslaw]
通讯作者: Truszczynski, Miroslaw
DOI: --
发表时间: 2019
期刊: Proceedings of the 21st International Symposium on Practical Aspects of Declarative Languages (PADL
影响因子: --
作者: [Lierler, Y.]
通讯作者: Lierler, Y.
DOI: 10.1017/s1471068420000265
发表时间: 2020-08
期刊: Theory and Practice of Logic Programming
影响因子: 1.4
作者: [Pedro Cabalar;Jorge Fandinno;Yuliya Lierler]
通讯作者: Pedro Cabalar;Jorge Fandinno;Yuliya Lierler
DOI: 10.1017/s1471068422000400
发表时间: 2022
期刊: Theory and Practice of Logic Programming
影响因子: 1.4
作者: [LIERLER, YULIYA]
通讯作者: LIERLER, YULIYA
共 19 条
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    • 批准号:
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    • 负责人:
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    • 资助金额:
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    • 项目类别:
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    • 资助金额:
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