Topic
Knowledge representation and reasoning
About: Knowledge representation and reasoning is a research topic. Over the lifetime, 20078 publications have been published within this topic receiving 446310 citations. The topic is also known as: KR & KR².
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TL;DR: It is shown that subsumption in the terminological logic of NikL is undecidable and thus that there are no complete algorithms for subsumption or classification in NIKL.
101 citations
TL;DR: In this article, the notion of treewidth has been applied to logic-based reasoning problems such as abduction, closed world reasoning, circumscription, and disjunctive logic programming.
101 citations
TL;DR: A novel and extensible model balancing the new dimension of semantic quality (as a functional quality metric) with a QoS metric is proposed, and it is demonstrated the utility of Genetic Algorithms to allow optimization within the context of a large number of services foreseen by the “Web of Services” vision.
Abstract: Ranking and optimization of web service compositions represent challenging areas of research with significant implications for the realization of the “Web of Services” vision. “Semantic web services” use formal semantic descriptions of web service functionality and interface to enable automated reasoning over web service compositions. To judge the quality of the overall composition, for example, we can start by calculating the semantic similarities between outputs and inputs of connected constituent services, and aggregate these values into a measure of semantic quality for the composition. This paper takes a specific interest in combining semantic and nonfunctional criteria such as quality of service (QoS) to evaluate quality in web services composition. It proposes a novel and extensible model balancing the new dimension of semantic quality (as a functional quality metric) with a QoS metric, and using them together as ranking and optimization criteria. It also demonstrates the utility of Genetic Algorithms to allow optimization within the context of a large number of services foreseen by the “Web of Services” vision. We test the performance of the overall approach using a set of simulation experiments, and discuss its advantages and weaknesses.
101 citations
TL;DR: Extended Fuzzy Cognitive Maps are proposed to represent causal relationships more naturally and computer simulation results indicate the effectiveness of the E-FCMs.
Abstract: Fuzzy cognitive maps (FCMs) have been proposed to represent causal reasoning by using numeric processing. They graphically represent uncertain causal reasoning. In the resonant states, there emerges a limit cycle or a hidden pattern, which is a FCM inference. However, there are some shortcomings concerned with knowledge representation in the conventional FCMs. The author proposes extended fuzzy cognitive maps (E-FCMs) to represent causal relationships more naturally. The features of the E-FCMs are nonlinear membership functions, conditional weights, and time delay weights. Computer simulation results indicate the effectiveness of the E-FCMs. >
101 citations
TL;DR: A new concept-learning method is proposed that learns new concepts from inference patterns, not from positive/negative examples that most conventional concept learning methods use, and automatically generates multilevel representations from a given physical/single-level representation of a carry-chain circuit.
101 citations