法律模糊性問題的“解碼”與“計算”

Decoding and Computing the Fuzzy Problems in the Field of Law

在法律實踐中，常常需要模糊推理和模糊判斷。由“模糊邏輯之父”拉特飛·紮德開創的模糊邏輯理論，提供了一種分析模糊性問題的新工具，可用以解析不確定法律概念，認定信息不完備條件下的待證事實，並作出模糊綜合評判。特別是紮德的“詞語計算”和“軟計算”理論，比較清晰地揭示了人類的思維過程，也使我們更容易理解法官的判案過程。這一過程可以概括為：“軟計算=貝葉斯法則+語言概率”，即用當事人雙方提供的證據所反映的信息，不斷修正、調整其主觀上以語言變量而非數值形式表示的概率性認識（置信度），經漸進收斂，對事實存在的可能性形成“內心確信”，然後據以作出裁判。

The world is not simply black and white, but has many fuzzy areas. In the existing legal logics, although there is no fuzzy logic concept, the fuzzy reasoning and fuzzy judgment are often needed in the legal practice. The fuzzy logic theory pioneered by L. A. Zad, father of fuzzy logic theory, provides a new tool for fuzzy analysis, which can be used to analyze the uncertain legal concepts, identify the fuzzy facts under the conditions of incomplete information, and make a fuzzy comprehensive judgment. In particular, Zad’s“word computing”and“soft computing”theories clearly reveal human thinking process and make it easier to understand judge’s decision process, which can be summarized as:“Soft Computing =Bayesian Law + Language Probability”, i. e. , with the information of the parties’evidence, a judge constantly adjust his subjective understanding in the form of language variables rather than numerical probability. Through the opinion convergence, the judge will reach his“moral certainty”about the possibility of some facts, and then according it to make the final judgment.