International Journal Of Approximate Reasoning SCIESCI

The International Journal of Approximate Reasoning is intended to serve as a forum for the treatment of imprecision and uncertainty in Artificial and Computational Intelligence, covering both the foundations of uncertainty theories, and the design of intelligent systems for scientific and engineering applications. It publishes high-quality research papers describing theoretical developments or innovative applications, as well as review articles on topics of general interest.

Relevant topics include, but are not limited to, probabilistic reasoning and Bayesian networks, imprecise probabilities, random sets, belief functions (Dempster-Shafer theory), possibility theory, fuzzy sets, rough sets, decision theory, non-additive measures and integrals, qualitative reasoning about uncertainty, comparative probability orderings, game-theoretic probability, default reasoning, nonstandard logics, argumentation systems, inconsistency tolerant reasoning, elicitation techniques, philosophical foundations and psychological models of uncertain reasoning.

Domains of application for uncertain reasoning systems include risk analysis and assessment, information retrieval and database design, information fusion, machine learning, data and web mining, computer vision, image and signal processing, intelligent data analysis, statistics, multi-agent systems, etc.

《国际近似推理杂志》旨在作为处理人工智能和计算智能中的不精确性和不确定性的论坛，涵盖不确定性理论的基础以及科学和工程应用的智能系统设计。它发表描述理论发展或创新应用的高质量研究论文，以及关于普遍感兴趣的主题的评论文章。

相关主题包括但不限于概率推理和贝叶斯网络、不精确概率、随机集、信念函数（Dempster-Shafer 理论）、可能性理论、模糊集、粗糙集、决策理论、非加法测量和积分、关于不确定性的定性推理、比较概率排序、博弈论概率、默认推理、非标准逻辑、论证系统、不一致性容忍推理、启发技术、不确定推理的哲学基础和心理模型。

不确定推理系统的应用领域包括风险分析和评估、信息检索和数据库设计、信息融合、机器学习、数据和网络挖掘、计算机视觉、图像和信号处理、智能数据分析、统计学、多智能体系统等

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