Nogood learning is a powerful approach to reducing search in Constraint Programming (CP) solvers. The current state of the art, called Lazy Clause Generation (LCG), uses resolution to derive nogoods expressing the reasons for each search failure. Such nogoods can prune other parts of the search tree, producing exponential speedups on a wide variety of problems. Nogood learning solvers can be seen as resolution proof systems. The stronger the proof system, the faster it can solve a CP problem. It has recently been shown that the proof system used in LCG is at least as strong as general resolution. However, stronger proof systems such as \emph{extended resolution} exist. Extended resolution allows for literals expressing arbitrary logical concepts over existing variables to be introduced and can allow exponentially smaller proofs than general resolution. The primary problem in using extended resolution is to figure out exactly which literals are useful to introduce. In this paper, we show that we can use the structural information contained in a CP model in order to introduce useful literals, and that this can translate into significant speedups on a range of problems.
Extended High Utility Pattern Mining: An Answer Set Programming Based Framework and Applications
Polytechnic University of Marche（马尔凯理工大学）；University of Calabria（卡拉布里亚大学）
从给定数据集中检测相关模式集是数据采掘中的一个重要挑战。模式的相关性，在文献中也称为效用，是一种主观的衡量标准，实际上可以从非常不同的角度进行评估。基于规则的语言，如答案集编程（ASP）似乎非常适合指定用户提供的标准，以评估模式效用的约束形式;此外，ASP的声明性允许在几个标准之间进行非常容易的切换，以便从不同的角度分析数据集。在本文中，我们采取步骤扩展的概念高效用模式挖掘（HUPM），特别是我们引入了一个新的框架，允许新的类的效用标准没有考虑在以前的文献。我们还展示了如何最近扩展的ASP与外部功能可以支持一个快速有效的编码和测试的新框架。为了证明所提出的框架的潜力，我们将其作为构建模块，用于定义预测COVID-19患者入住ICU的创新方法。最后，一个广泛的实验活动从定量和定性的角度证明了所提出的方法的有效性。逻辑程序设计理论与实践（Theory and Practice of Logic Programming，TPLP）
Extended ASP tableaux and rule redundancy in normal logic programs
Helsinki University of Technology (TKK)（赫尔辛基理工大学（TKK））
我们介绍了一个扩展的tableau演算的答案集编程（ASP）。证明系统基于[Gebser&Schaub，ICLP 2006]中定义的ASP表，并添加了扩展规则。我们从理论和经验两方面研究了扩展ASP表的功能。本文研究了扩展ASP表与Tseitin定义的子句集扩展归结证明系统的关系，并通过对一类正规逻辑程序P_n给出多项式长度证明，将扩展ASP表与ASP表分开，其中ASP表具有关于n的指数长度极小证明.此外，扩展ASP表格意味着有趣的洞察力的影响，程序简化的长度证明在ASP。密切相关的扩展ASP表格，我们实证研究的ASP解决效率的冗余规则的效果。逻辑程序设计理论与实践（Theory and Practice of Logic Programming，TPLP）
A Linear Programming Approach for Resource-Aware Information-Theoretic Tree Abstractions
Georgia Institute of Technology（佐治亚理工学院）；The University of North Carolina at Charlotte（北卡罗来纳大学夏洛特分校）；Institute for Robotics and Intelligent Machines（机器人与智能机器研究所）
