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引用次数: 9

摘要

作者提出了一种将Prolog的模式匹配与一种新颖的逻辑和分辨率控制方法相结合的编程系统。节点和弧的网络与三值逻辑一起用来表示谓词和它们的结果之间的联系,并表示从理论的事实和命题到定理的流动。通过这种方式,人们可以在这个“神经逻辑网络”中正确地处理不确定性和否定性。神经逻辑程序由特定的网络片段组成,这些网络片段被标记为谓词和弧权值,它们可以动态连接以形成推理链树。神经逻辑计算模型的架构是开放的,作者并不打算将模型从字面上解释为物理架构。
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Neural logic programming
The authors propose a programming system that combines pattern matching of Prolog with a novel approach to logic and the control of resolution. A network of nodes and arcs together with a three-valued logic is used to indicate the connections between predicates and their consequents, and to express the flow from facts and propositions of a theory to its theorems. In this way, one can handle uncertainty and negation properly in this 'neural logic network.' A neural logic program consists of a specification of network fragments, labeled with predicates and arc weights, and they can be joined dynamically to form a tree of reasoning chains. The architecture of the neural logic computational model is left open and the authors do not intend the model to be interpreted literally as a physical architecture.<>
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