JP7301034B2 - 準ニュートン信頼領域法を用いたポリシー最適化のためのシステムおよび方法 - Google Patents

準ニュートン信頼領域法を用いたポリシー最適化のためのシステムおよび方法 Download PDF

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JP7301034B2
JP7301034B2 JP2020159841A JP2020159841A JP7301034B2 JP 7301034 B2 JP7301034 B2 JP 7301034B2 JP 2020159841 A JP2020159841 A JP 2020159841A JP 2020159841 A JP2020159841 A JP 2020159841A JP 7301034 B2 JP7301034 B2 JP 7301034B2
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policy
function
controller
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objective function
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JP2021060988A5 (cg-RX-API-DMAC7.html
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ジャー・デベシュ
ラフナサン・アルビンド
ロメレス・ディエゴ
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Mitsubishi Electric Corp
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • G05B13/029—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks and expert systems
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Program-controlled manipulators
    • B25J9/16—Program controls
    • B25J9/1628—Program controls characterised by the control loop
    • B25J9/163—Program controls characterised by the control loop learning, adaptive, model based, rule based expert control
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/047—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators the criterion being a time optimal performance criterion
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/0499—Feedforward networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/092—Reinforcement learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computing arrangements based on specific mathematical models
    • G06N7/01—Probabilistic graphical models, e.g. probabilistic networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/004—Artificial life, i.e. computing arrangements simulating life
    • G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Artificial Intelligence (AREA)
  • General Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • Software Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Mathematical Physics (AREA)
  • Data Mining & Analysis (AREA)
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  • General Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Molecular Biology (AREA)
  • General Health & Medical Sciences (AREA)
  • Computational Linguistics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Computational Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Pure & Applied Mathematics (AREA)
  • Algebra (AREA)
  • Probability & Statistics with Applications (AREA)
  • Mathematical Optimization (AREA)
  • Robotics (AREA)
  • Mechanical Engineering (AREA)
  • Feedback Control In General (AREA)
JP2020159841A 2019-10-04 2020-09-24 準ニュートン信頼領域法を用いたポリシー最適化のためのシステムおよび方法 Active JP7301034B2 (ja)

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US16/592,977 2019-10-04
US16/592,977 US11650551B2 (en) 2019-10-04 2019-10-04 System and method for policy optimization using quasi-Newton trust region method

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JP2021060988A5 JP2021060988A5 (cg-RX-API-DMAC7.html) 2023-04-06
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CN110088775B (zh) * 2016-11-04 2023-11-07 渊慧科技有限公司 使用加强学习的环境预测
WO2020137019A1 (ja) * 2018-12-27 2020-07-02 日本電気株式会社 方策作成装置、制御装置、方策作成方法、及び、方策作成プログラムが格納された非一時的なコンピュータ可読媒体
US11992945B2 (en) * 2020-11-10 2024-05-28 Google Llc System and methods for training robot policies in the real world
JP7556276B2 (ja) * 2020-12-02 2024-09-26 富士通株式会社 量子化プログラム,量子化方法および量子化装置
KR20230157488A (ko) * 2021-05-28 2023-11-16 딥마인드 테크놀로지스 리미티드 가중 정책 프로젝션을 사용한 다중 목적 강화 학습
US20220414531A1 (en) * 2021-06-25 2022-12-29 International Business Machines Corporation Mitigating adversarial attacks for simultaneous prediction and optimization of models
US12313276B2 (en) * 2022-04-21 2025-05-27 Mitsubishi Electric Research Laboratories, Inc. Time-varying reinforcement learning for robust adaptive estimator design with application to HVAC flow control
CN115042174B (zh) * 2022-06-07 2024-08-30 中国北方车辆研究所 一种分层驱动的自主无人系统类人控制架构
JP2024118220A (ja) * 2023-02-20 2024-08-30 富士通株式会社 強化学習プログラム、情報処理装置および強化学習方法
JP2024148223A (ja) * 2023-04-05 2024-10-18 富士通株式会社 強化学習プログラム、強化学習方法、および情報処理装置
CN117162086B (zh) * 2023-08-07 2024-07-05 南京云创大数据科技股份有限公司 一种用于机械臂目标寻找的训练方法、方法及训练系统
WO2025160824A1 (zh) * 2024-01-31 2025-08-07 电子科技大学(深圳)高等研究院 基于人工智能的直流-直流转换器自适应控制方法及设备
CN117674595B (zh) * 2024-01-31 2024-06-18 电子科技大学(深圳)高等研究院 基于人工智能的直流-直流转换器自适应控制方法及设备
CN118721205B (zh) * 2024-07-24 2025-01-28 华中科技大学 一种机械臂运动规划方法及系统

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2009289199A (ja) 2008-05-30 2009-12-10 Okinawa Institute Of Science & Technology 制御器、制御方法および制御プログラム
US20170286840A1 (en) 2016-04-04 2017-10-05 Financialsharp, Inc. System and method for performance evaluation of probability forecast

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9434389B2 (en) * 2013-11-18 2016-09-06 Mitsubishi Electric Research Laboratories, Inc. Actions prediction for hypothetical driving conditions
WO2019012437A1 (en) 2017-07-13 2019-01-17 Anand Deshpande SOUND DEVICE BASED ON MONITORING OF MACHINE USES AND METHOD OF OPERATING SAME

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2009289199A (ja) 2008-05-30 2009-12-10 Okinawa Institute Of Science & Technology 制御器、制御方法および制御プログラム
US20170286840A1 (en) 2016-04-04 2017-10-05 Financialsharp, Inc. System and method for performance evaluation of probability forecast

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
金森 敬文,機械学習のための連続最適化,株式会社講談社 鈴木 哲,2016年,107-142頁

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