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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20 May 2003
TL;DR: In this article, the authors present a rule-based approach to representation of business contracts that enables software agents to create, evaluate, negotiate, and execute contracts with substantial automation and modularity.
Abstract: SweetDeal is a rule-based approach to representation of business contracts that enables software agents to create, evaluate, negotiate, and execute contracts with substantial automation and modularity. It builds upon the situated courteous logic programs knowledge representation in RuleML, the emerging standard for Semantic Web XML rules. Here, we newly extend the SweetDeal approach by also incorporating process knowledge descriptions whose ontologies are represented in DAML+OIL (emerging standard for Semantic Web ontologies) thereby enabling more complex contracts with behavioral provisions, especially for handling exception conditions (e.g., late delivery or non-payment) that might arise during the execution of the contract. This provides a foundation for representing and automating deals about services -- in particular, about Web Services, so as to help search, select, and compose them. Our system is also the first to combine emerging Semantic Web standards for knowledge representation of rules (RuleML) with ontologies (DAML+OIL) for a practical e-business application domain, and further to do so with process knowledge. This also newly fleshes out the evolving concept of Semantic Web Services. A prototype (soon public) is running.
152 citations
04 Aug 2008
TL;DR: This paper presents the plan of building the large knowledge collider, a platform for massive distributed incomplete reasoning that will remove scalability barriers, and discusses how the technologies of LarKC would move beyond the state-of-the-art of Web scale reasoning.
Abstract: Current semantic Web reasoning systems do not scale to the requirements of their hottest applications, such as analyzing data from millions of mobile devices, dealing with terabytes of scientific data, and content management in enterprises with thousands of knowledge workers. In this paper, we present our plan of building the large knowledge collider, a platform for massive distributed incomplete reasoning that will remove these scalability barriers. This is achieved by (i) enriching the current logic-based semantic Web reasoning methods, (ii) employing cognitively inspired approaches and techniques, and (iii) building a distributed reasoning platform and realizing it both on a high-performance computing cluster and via "computing at home". In this paper, we will discuss how the technologies of LarKC would move beyond the state-of-the-art of Web scale reasoning.
152 citations
TL;DR: This work studied 11 types of guideline representation models that can be used to encode guidelines in computer-interpretable formats and consistently found that primitives for representation of actions and decisions are necessary components of a guideline representation model.
151 citations
TL;DR: It is shown that the epistemic operator formalizes procedural rules, as provided in many knowledge representation systems, and enables sophisticated query formulation, including various forms of closed-world reasoning.
151 citations
TL;DR: This work presents an overview of the improved FPN theories and models from the perspectives of reasoning algorithms, knowledge representations and FPN models, and offers directions for future research to improve the FPN performance.
151 citations