Construction of Fuzzy Inference System with AI-Neuro Based Autonomous Learning Abilities and Verification of Its Effectiveness

基于人工智能神经自主学习能力的模糊推理系统构建及其有效性验证

• 批准号: 03650349
• 负责人: KATAI Osamu
• 金额: $ 1.34万
• 依托单位: KYOTO UNIVERSITY
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for General Scientific Research (C)
• 财政年份: 1991
• 资助国家: 日本
• 起止时间: 1991 至 1993
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-03650349/
• 关键词: Fuzzy Inference; Constraint-Oriented Problem Solving; Fuzzy Control; Symbolic Processing; Neural Network; Genetic Alogorithm; Machine Learning; Autonomous Decentralized System; 制約充足問題; 自己組織化; 自律移動ロボット; ファジイ集合; ファジイ推論; 制約指向; 信号処理; ファジィ集合; オ

From constraint-oriented perspectives, a new concept of fuzziness is introduced, and based on this concept, new method of fuzzy inference is formalized, which is then shown to be able to be coupled tightly with symbolic procesing in AI that is based two-valued logic. This new method of combined inference is then applied to sensing information processing and image understanding under incomplete information, and also to planning and its execution of autonomous mobile robot. Moreover, the combined inference is applied to control of inverted pendulum, which elucidates its effectiveness. Also, new programming environment for this inference system is introduced by using CLP(R), a kind of constraint logic programming language. By using machine learning techniques, a learning method for acquiring fuzzy inference rules is introduced, whose results are then refined and organized by neural networks and genetic algorithms. Finally, the total system for fuzzy inference with automomous learning abilities is applied to control and planning of autonomous mobile robots, which elucidates the effectiveness of our approach.

从面向约束的角度来看，引入了一个新的模糊概念，并基于此概念，新的模糊推理方法是形式化的，然后被证明可以与AI中的符号策略紧密耦合，该方法基于AI的象征性，该方法基于两种值的值。逻辑。然后将这种新的合并推理方法应用于不完整信息下的感测信息处理和图像理解，以及计划及其执行自主移动机器人。此外，将组合的推理应用于控制摆的倒置，这阐明了其有效性。此外，通过使用CLP（R）介绍了此推理系统的新编程环境，这是一种约束逻辑编程语言。通过使用机器学习技术，引入了一种用于获取模糊推理规则的学习方法，然后通过神经网络和遗传算法对其结果进行了完善和组织。最后，使用自动学习能力的自动移动机器人的控制和计划，用于控制和计划，这阐明了我们方法的有效性。

项目成果

日本ファジィ学会(編): "知識情報処理とファジィ" 日刊工業新聞社, 283 (1993)

日本模糊学会（主编）：《知识信息处理与模糊》日刊工业新闻，283（1993）

O.Katai: "Formalization of Fuzzy Set Concept and Fuzzy Inference Based on Order-Constraint Structures" Transactions of the Society of Instrument and Conrol Engineers. Vol.28. 30-39 (1992)

O.Katai：“基于阶次约束结构的模糊集概念和模糊推理的形式化”仪器与控制工程师学会会刊。

O.Katai: "Synergetic Computation for Constraint Satisfaction Problems Involving Continuous and Fuzzy Varaibles by Using Occam" Transputer/Occam 4. 146-160 (1992)

O.Katai：“使用奥卡姆对涉及连续和模糊变量的约束满足问题进行协同计算” Transputer/Occam 4. 146-160 (1992)

片井 修: "区間制約ファジイ推論法による倒立振子の制御と車両移動計画の生成" 計測自動制御学会論文集. 第29巻. 470-479 (1993)

Osamu Katai：“使用区间约束模糊推理控制倒立摆和生成车辆运动计划”《仪器与控制工程师学会汇刊》，第 29 卷，470-479 (1993)

T.Sawaragi: "Signal Understanding of Spectrum Data Using Bayesian Network and Neural Network" Proc.of 1993 Int.Joint Conference on Neural Networks. Vol.2. 1909-1910 (1993)

T.Sawaragi：“使用贝叶斯网络和神经网络对频谱数据进行信号理解”Proc.of 1993 Int.Joint Conference on Neural Networks。