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首页> 外文期刊>International Journal of Pattern Recognition and Artificial Intelligence >LOGICAL REASONING VIA SATISFIABILITY MAPPED INTO ENERGY FUNCTIONS
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LOGICAL REASONING VIA SATISFIABILITY MAPPED INTO ENERGY FUNCTIONS

机译：通过映射到能量函数的可满足性进行逻辑推理

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摘要

This paper presents the implementation of ARQ-PROP II, a limited-depth propositional neural reasoner based on the Resolution Principle. The SATyrus platform was used in the synthesis of Energy functions from a set of pseudo-Boolean constraints specifying ARQ-PROP II architectures for different inferencing depths. Global minima of the Energy functions produced by SATyrus are associated to SATisfiability of a formula and, in the case of ARQ-PROP II, are associated to Resolution-based refutations. This allows for simplified abduction, prediction and planning to be unified with deduction in a goal-driven style, i.e. there is no need for presetting a reasoning style upon a target set of clauses. Experimental results on deduction with ARQ-PROP II using different propositional depth settings are presented together with a correction of Gadi Pinkas' mapping of SATisfiability into Energy minima.
机译：本文介绍了基于解析原理的有限深度命题神经推理器ARQ-PROP II的实现。 SATyrus平台用于从一组伪布尔约束中综合能量函数，这些伪布尔约束指定了针对不同推理深度的ARQ-PROP II体系结构。 SATyrus产生的能量函数的全局最小值与公式的可满足性相关，在ARQ-PROP II的情况下，与基于分辨率的驳回相关。这允许简化的绑架，预测和计划与以目标驱动的方式进行演绎统一，即无需在目标子句集上预设推理方式。提出了使用不同命题深度设置进行ARQ-PROP II演绎的实验结果，以及对Gadi Pinkas将SATisfiability映射为Energy minima的修正。

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