Probability theory captures a number of essential characteristics of human cognition, including aspects of perception, reasoning, belief revision, and learning. 机率理论涵盖了人类认知中的许多重要特徵,包括感知、推理、信念改变和学习方面。
The main work of this paper can be divided into three parts: ( 1) The first part of this paper presents several representative iterative belief revision methods, and compare them to AGM postulates. 首先介绍几种典型的迭代修正方法。并对这些方法进行比较,讨论他们满足AGM公设的情况。
Handling inconsistent information is an essential problem in belief revision. 信念修正中一个关键的问题就是对不一致信息的处理。
A Complete and Operational Approach to Belief Revision 信念修正的完全和可操作的方法
The theory of belief revision describes how the beliefs of an agent should change upon receiving the new information. 信念修正主要解决在接收到新信息时,如何对原有知识库进行操作的问题。
There are many different frameworks for belief revision but AGM [ 1] is the most notable one. 在信念修正问题的研究中,学者们提出了许多不同的框架,其中最有影响力的就是AGM[1]理论。
The Research of Multi-agent Belief Revision 多Agent信念修正研究
Believability based Iterated Belief Revision 一种基于可信度的迭代信念修正方法
This paper presents the sequential belief revision method to eliminate information asymmetry in supply chains. 提出了使用序贯信念修正方法来削弱供应链中的信息不对称现象。
Speculative Computation Based on Master Agent Belief Revision and Its Resource Negotiation 基于主Agent信念修正的推测计算及其资源协商
We embed Bayes learning mechanism on the basis of the negotiation model, and elaborate process descriptions of evaluating offers, belief revision and proposing counter-offers are presented. 在该协商模型的基础上引入贝叶斯学习机制,并分别对更新信念、生成提议等协商过程作了详细阐述。
A persuasive multi-agent multi-issue negotiation method is illustrated, which is underpinned by belief revision logic. 提出一种劝说式多Agent多议题协商方法。
One is to revise the old beliefs in order to keep the consistency of the knowledge base, i.e. belief revision methods [ 1-10]. 一种是修正原有知识库中的信念以保持新信念加入后的知识库的一致性,即信念修正的方法[1-10]。
Multiple user preferences information merging algorithm based on total distance minimization is designed according to belief revision theory. The algorithm satisfied IC ( Integrity Constraints) postulates and Majority postulate in belief revision theory. 根据信念修正理论设计了基于总体距离最小的多用户偏好信息的融合算法,该算法满足信念修正理论中带完整性约束的基本公设以及Majority公设。
A Computational Method of General Belief Revision 一种广义信念修正的计算方法
The AGM Theory for Belief Revision 信念修正的AGM理论
Classical iterated belief revision methods mainly focus on the consistency of belief change, with little concern of the impact of the uncertain information in multi-agent system and the process of revision. 经典的迭代信念修正主要关注信念修正的一致性,并未考虑多agent系统中信息具有不可靠性,以及信念修正过程对修正结果的影响。
The problem of belief revision is a lively subject, which contains various theories. 信念修正问题是一个富有活力的,正在发展的研究主题。
In addition, main existing belief revision algorithms are studied while their shortages are pointed out. ( 2) Basic assumption and framework are researched in details. 对目前主要的修正算法进行了研究,并指出了其存在的不足。(2)提出和实现了依赖信念改变算法。
The main work of this paper is stated as follows: ( 1) Fully investigate and analyze the existing belief revision assumption, and then select the proper hypothesis combination suited to guide belief revision algorithm as the research foundation of belief revision. 主要工作和创新包括以下几点:(1)对现有的主要信念修正假设作了充分研究和分析,选择出适合指导信念改变算法的假设组合作为研究改变算法的基础。
Through revising the original belief states to obtain a new consistent belief is just the meaning of belief revision. 如何对已有的信念状态进行修正,从而获得一个一致的新的信念状态,这就是信念修正。
Our results suggest: auditors adjust their belief as the audit evidences updates. The stronger of the audit evidences, the bigger magnitude of belief revision. 实验结果表明:注册会计师随着审计证据的更新不断的调整其信念值,审计证据越强,信念调整幅度越大。
The main thought of belief revision is about sorting the belief based on some assumption and using more reliable belief to revise the less reliable belief. Finally the following method can obtain the consistent belief set. 该方法的主要思想是首先根据一定的假设对信念进行排序,然后用较可靠的信念去修正不够可靠的信念,最后得到一致的信念集。
In this model, formulas denote beliefs and formula sets denote beliefs sets. Dependent belief revision algorithm is adopted in belief revision and action reasoning. 该模型使用公式表示信念,用公式的集合表示信念集,用依赖信念修正算法进行信念修正,用依赖信念更新算法进行行动推理。
Recently modern logic has been used widely and developed rapidly in the areas of studying knowledge update, belief revision and preference upgrade etc., then the modern logic becomes the efficient theoretic tool to resolve the problem of aggregating collective rationality. 近年来,现代逻辑理论在知识更新、信念修正以及偏好升级等问题的研究中得到了广泛应用与快速发展,从而为探究群体理性聚合难题提供了有效的理论分析工具。
Through this study, the problems which exist in the belief revision method are able to be avoided by using the non-revision method, and the range of the non-revision method application is expanded. 通过本文的研究,不仅证明了信念静态非修正方法可以解决信念修正方法中存在的一些问题,同时也扩大了信念静态非修正方法的应用范围。
At present, the belief revision method is one of the most important methods in coordinating to handle the inconsistent beliefs. 目前,对不一致信念进行协调性处理的一个主要方法是信念修正方法。
Belief revision is the process that changing original beliefs of an agent to accept new, more precise and more reliable information which may inconsistent with existing beliefs. 信念改变包括信念更新和信念修正,是指改变智能体原有信念来接受更新,更准确,更可靠,并且有可能与原来信念不一致的信息的过程。
Belief revision is a process during which a rational agent change the belief state from inconsistency into consistency. 信念调整指的是一个理性主体将信念从一种状态转变为另一种状态的过程。
Based on all above, it using a lab research discussed auditors 'belief revision in different response mode. 在上述分析的基础之上,文章通过一项实验研究,讨论了我国注册会计师在不同反应模式下的信念调整。