degree of belief造句

• The properties of ramsey ' s concept of degree of belief
  拉姆齐信念度概念的性质
• Expressions of degree of belief were used in language long before people began codifying the laws of probability theory
  在人们开始编制机率法则之前，信念程度的表达很早就已经在语言中使用了。
• The classical dutch book argument shows that the agent surely loses if his degrees of belief in propositions do not satisfy the laws of the probability
  摘要经典荷兰赌论证表明：如果当事人的不确定信念度赋值不满足概率论公理，那么他在某一赌局中总是输。
• Repeat until the decision tree generate . delete the branch whose degree of belief is less then the designated value and lastly get the ideal decision
  再剪除可信度小于规定最小可信度的规则所对应的分枝,最后得到较为理想的决策树,综合所有规则进而得到诊断模型。
• The results show that the coherence in a partial belief system means that the assignments of values and degrees of belief are consistent with the ordering of preference
  荷兰赌论证意味着，在当事人的不确定信念系统中，有关定性和定量概念之间没有协调性：其价值和信念度赋值是混乱的，并导致非理性决策。
• Professor deng has developed a non - revision method which describes the credible degree of belief by quantitative method . since this method uses the quantitative information to describe the reliable degree of knowledge , it dose not deal with the inconsistent knowledge and uses the heuristic information to instruct reasoning that can make the result by reasoning among source knowledge the most reliable conclusion
  邓安生提出定量非修正方法，该方法避免了在信念修正过程中所产生的有用信息丢失的现象；并将在已有的信念之下能够推出的最为可靠的结论作为系统的最终结论，使得系统具有唯一的结论集，从而完全解决了系统在含有不一致信念的情况下结论难于选择的问题。
• 16 parsons s , giorigini p . an approach to using degrees of belief in bdi agents . information , uncertainty and fusion , kluwer academic publisher , 2000 , pp . 81 - 92 . 17 parsons s , sierra c , jennings n r . agents that reason and negotiate by arguing
  本文的工作，一方面把我们以前的概率逻辑程序语言扩展到了面向agent的情况进一步的，这种逻辑语言也扩展了hindriks等人的工作，即把面向agent的逻辑程序语言扩展到了面向不确定agent的情况，实现了对于不确定信息的动态的描述和推理。
• With the rapid development of computer network and communication technology , a great deal of information which comes from different domains is comprehended and accepted by people via computers . and along with the higher demand the captured information and the communication exchanges more frequently , the information semantic integration is needed in computers ’ sharing data . uncertainty knowledge becomes more prevalent in many application . probability theory has been proved to be one of the most powerful approaches to capture the degree of belief about uncertain knowledge . bayesian network ( bn ) , also called bayesian belief network , are widely - used approaches in probability theory at all times . with the development of the semantic web , ontology has become widely used to represent the conceptualization of a domain . ontology mapping has widely relied on the ontology semantic integration
  随着计算机网络和信息技术的高速发展,不同知识领域的大量信息需要人们通过计算机来理解和接受,而且随着人们对信息获取的要求越来越高,以及信息间数据交换的日益频繁,需要对计算机之间的信息交换进行语义级的合成。不确定性知识也得到了越来越普遍的应用和发展。概率理论已经被证明是获得非确定性知识的置信度的最有力方法之一。