Feature Similarity, Category Labels, and Causal Relations in Inductive Reasoning 特征相似性、类别标签与因果关系在归纳推理中的作用
All the causal reasoning can only be rationally justified on the basis of the assumption of an immutable causal order but cannot be justified by reference to evidence by empirical investigation. 所有的因果推理只能以一个不变的因果顺序假定为基础做出理性判断,而无法参考实证研究的证据进行判断。
Causal reasoning may go from cause to effect or from effect to cause. 原因的推理可以从原因到结果或结果到原因。
Bayesian Networks for Causal Reasoning in Situation Assessment 用于态势评估中因果推理的贝叶斯网络
Principles and algorithms for causal qualitative reasoning of geometric objects 几何因果定性推理的基本原理和算法
The Relation between Counterfactual Thinking and Causal Reasoning 反事实思维与因果推理的关系
Because of the ability to solve indeterminate problems and do well in the causal reasoning, Bayesian network has been the primary technique for causal datum mining, and an important way to realize the estimation of distribution algorithms. 贝叶斯网络因其处理不确定性问题的能力及其良好的因果推理机制已成为因果数据采掘的主要技术,同样,它也是实现分布估计算法的一个重要途径。
And it finally extends and utilizes these abstract reasoning models to formalize causal knowledge in specific domains to develop practical causal reasoning systems for AI research, e. 最后它把因果推理模型推广应用到具体的领域以建立实际的AI系统,例如在故事理解和法律推理中的应用。
A causal reasoning method 一种因果推理形式
An Overview on Qualitative Reasoning(ⅰ)── Commonsense Reasoning, Causal Explanation and Classical Qualitative Reasoning Methods 定性推理综述(Ⅰ)&常识知识推理和因果性解释以及传统定性推理方法
Training Studies on Rule-based Causal Reasoning in Children Aged 3 to 4 Years 3~4岁儿童规则因果推理能力的训练研究
It constructs computational frameworks for abstract causal reasoning models, such as causal prediction, causal explanation, and causal diagnosis; 它构造了基于事件的因果关系的抽象推理模型,特别是因果预测、因果解释和因果诊断;
A Causal Reasoning Method Based on Object-Oriented Environment 一种基于面向对象环境的因果推理方法
Our system adopts tree hierarchy semantic network and causal network model according to different knowledge content, applys inexact mixed reasoning to enhance the veracity of the result. 系统根据蔬菜栽培知识的内容不同分别采用了树形层次语义网络和因果网络模型两种知识表示形式,并运用了不精确混合推理策略,使得系统推理更快更准确。
Dfcr: a formal framework for causal reasoning DFCR:因果推理的一种形式框架
Therefore, Kant shows that uniformity of nature, as a premise of causal reasoning, is a transcendental principle, and it is a necessary truth for any possible experiences. 从而证明了作为因果推理前提的自然齐一性是一条先验原理,其对一切可能经验具有必然性。
This paper presents two main applications of causal reasoning: to predict indirect facts of actions and to find the actual cause of some given facts. We point out that logic is not adequate for solving these two problems. 本文介绍了因果推理的两个主要应用:预测行为的间接结果,找出给定事实的真正原因,指出了用逻辑描述的因果关系在解决这两个问题中存在的不足。
Indeterminacy Causal Inductive Automatic Reasoning Mechanism Based On Fuzzy State Describing 基于模糊状态描述的不确定因果归纳自动推理机制
As last, we contrast methods which implement intelligence based on logic and those based cognitive science, point out that causal reasoning should be performed in the framework of cognitive science. 本文最后比较了基于逻辑的方法和基于认知科学的方法实现智能的区别,指出了因果推理应该在认知科学的框架内得到解决。
Causal Knowledge Representation and Nonmonotonic Reasoning Models in Law Consultant Systems 法律知识的因果表达和非单调推理模型
A method of causal ordering reasoning under stochastic context 随机环境下的因果推理方法
APPLICATION OF MULTI-SCALE QUALITATIVE CAUSAL REASONING TO PROCESS MONITORING An APProach to Qualitative Decision-making Modeling 生产过程监测的多尺度定性特征因果推理方法定性决策模型初探
Pearl's method in dealing with causal reasoning, which treats causation as a computational schema. This idea of treating intelligence as computational schema is the basic idea of cognitive science. Pearl提出的因果推理方法,该方法的基本思想是把因果推理看成是一种计算模式,而这种把智能归结为计算模式的想法正是认知科学中的核心思想。
This study adopted the general pattern of logical reasoning with causal conditions to research the development of childrenren's social information reasoning with causal conditions. 采用因果条件性逻辑推理研究的一般模式,研究了儿童社会信息因果推理发展状况。
Specific causal reasoning systems are constructed. 单调性。(4)以默认规则表达方法为基础,建立了具体领域的因果推理应用模型。
Causal reasoning has probability, not necessity. 我们进行因果推断,不具有必然性,只具有或然性,我们进行因果推断是由于习惯而发生的。
Counterfactual thinking is a way of thinking in our everyday life, which influence causal reasoning and attribution. 反事实思维是人们日常生活中经常产生的一种思维方式,这种思维常常影响因果推理和归因。
Causal reasoning is integrated into the multi-agent model and employed in modeling and simulation of team effectiveness. The simulation model is developed into an integrated simulation system based on Repast. 在多Agent模型中集成因果推理,对团队有效性进行建模与模拟,并开发了基于Repast的集成模拟系统。
The approach of upgraded cellular automata integrated with causal reasoning is used for modeling and simulation of employee-task interactions. The model is implemented into a simulation system. 将经过改进的元胞自动机与因果推理集成,对员工与任务互动过程建模与模拟,并实现为模拟系统。