Answer set programming (ASP) is a popular declarative programming paradigm with a wide
range of applications in artificial intelligence. Oftentimes, when modeling an AI problem with …

Answer set programming is a form of declarative programming widely used to solve difficult
search problems. Probabilistic applications however require to go beyond simple search for …

Minimal models of a Boolean formula play a pivotal role in various reasoning tasks. While
previous research has primarily focused on qualitative analysis over minimal models; our …

Although propositional model counting (# SAT) was long considered too hard to be practical,
today's highly efficient solvers facilitate applications in probabilistic reasoning, reliability …

Knowledge Representation and Reasoning is a central, longstanding, and active area of
Artificial Intelligence. Over the years it has evolved significantly; more recently it has been …

[目的] 充分融合自然语言句子的深层语义表示和表层语法结构, 实现语义和语法的互补.[方法]
提出基于规则串联的抽象语义表示和依存语法集成策略, 并进行方面级情感分析 …

Counting the number of models of a Boolean formula is a fundamental problem in artificial
intelligence and reasoning. Minimal models of a Boolean formula are critical in various …

Cognitive theories for reasoning are about understanding how humans come to conclusions
from a set of premises. Starting from hypothetical thoughts, we are interested which are the …

Answer Set Programming (ASP) has emerged as a promising paradigm in knowledge
representation and automated reason-ing owing to its ability to model hard combinatorial …

Abstract Answer Set Programming (ASP) is a prominent problem-modeling and solving
framework, whose solutions are called answer sets. Epistemic logic programs (ELP) extend …