找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Inductive Biases in Machine Learning for Robotics and Control; Michael Lutter Book 2023 The Editor(s) (if applicable) and The Author(s), u

[復(fù)制鏈接]
查看: 25598|回復(fù): 36
樓主
發(fā)表于 2025-3-21 17:30:39 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Inductive Biases in Machine Learning for Robotics and Control
編輯Michael Lutter
視頻videohttp://file.papertrans.cn/464/463880/463880.mp4
概述Presents recent research on Inductive Biases in Machine Learning for Robotics and Control.Interesting for postgraduates and researchers working or wanting to learn more on robot learning with inductiv
叢書名稱Springer Tracts in Advanced Robotics
圖書封面Titlebook: Inductive Biases in Machine Learning for Robotics and Control;  Michael Lutter Book 2023 The Editor(s) (if applicable) and The Author(s), u
描述.One important robotics problem is “How can one program a robot to perform a task”? Classical robotics solves this problem by manually engineering modules for state estimation, planning, and control. In contrast, robot learning solely relies on black-box models and data. This book shows that these two approaches of classical engineering and black-box machine learning are not mutually exclusive. To solve tasks with robots, one can transfer insights from classical robotics to deep networks and obtain better learning algorithms for robotics and control. To highlight that incorporating existing knowledge as inductive biases in machine learning algorithms improves performance, this book covers different approaches for learning dynamics models and learning robust control policies. The presented algorithms leverage the knowledge of Newtonian Mechanics, Lagrangian Mechanics as well as the Hamilton-Jacobi-Isaacs differential equation as inductive bias and are evaluated on physical robots..
出版日期Book 2023
關(guān)鍵詞Robotics; Robot Learning; Inductive Biases; Control; Machine Learning
版次1
doihttps://doi.org/10.1007/978-3-031-37832-4
isbn_softcover978-3-031-37834-8
isbn_ebook978-3-031-37832-4Series ISSN 1610-7438 Series E-ISSN 1610-742X
issn_series 1610-7438
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

書目名稱Inductive Biases in Machine Learning for Robotics and Control影響因子(影響力)




書目名稱Inductive Biases in Machine Learning for Robotics and Control影響因子(影響力)學(xué)科排名




書目名稱Inductive Biases in Machine Learning for Robotics and Control網(wǎng)絡(luò)公開度




書目名稱Inductive Biases in Machine Learning for Robotics and Control網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Inductive Biases in Machine Learning for Robotics and Control被引頻次




書目名稱Inductive Biases in Machine Learning for Robotics and Control被引頻次學(xué)科排名




書目名稱Inductive Biases in Machine Learning for Robotics and Control年度引用




書目名稱Inductive Biases in Machine Learning for Robotics and Control年度引用學(xué)科排名




書目名稱Inductive Biases in Machine Learning for Robotics and Control讀者反饋




書目名稱Inductive Biases in Machine Learning for Robotics and Control讀者反饋學(xué)科排名




單選投票, 共有 0 人參與投票
 

0票 0%

Perfect with Aesthetics

 

0票 0%

Better Implies Difficulty

 

0票 0%

Good and Satisfactory

 

0票 0%

Adverse Performance

 

0票 0%

Disdainful Garbage

您所在的用戶組沒有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-21 20:27:05 | 只看該作者
板凳
發(fā)表于 2025-3-22 01:00:20 | 只看該作者
地板
發(fā)表于 2025-3-22 04:40:06 | 只看該作者
Springer Tracts in Advanced Roboticshttp://image.papertrans.cn/i/image/463880.jpg
5#
發(fā)表于 2025-3-22 09:33:56 | 只看該作者
Continuous-Time Fitted Value Iteration for Robust Policies,ient and necessary condition for optimality?[.]. Solving the yields the optimal value function, which can be used to retrieve the optimal action at each state. Therefore, this ansatz has been used by various research communities, including economics?[., .] and robotics?[., ., ., .], to compute the optimal plan for a given reward function.
6#
發(fā)表于 2025-3-22 14:39:00 | 只看該作者
https://doi.org/10.1007/978-3-031-37832-4Robotics; Robot Learning; Inductive Biases; Control; Machine Learning
7#
發(fā)表于 2025-3-22 18:11:57 | 只看該作者
Book 2023d learning robust control policies. The presented algorithms leverage the knowledge of Newtonian Mechanics, Lagrangian Mechanics as well as the Hamilton-Jacobi-Isaacs differential equation as inductive bias and are evaluated on physical robots..
8#
發(fā)表于 2025-3-23 00:38:21 | 只看該作者
9#
發(fā)表于 2025-3-23 03:50:47 | 只看該作者
10#
發(fā)表于 2025-3-23 05:43:19 | 只看該作者
Michael Lutterss probable reasons for the relatively moderate success and acceptance of model-based performance and dependability evaluation. What did we do right, what did we do wrong? Which circumstances led to successes, and where did we fail?.Based on the gathered insights, I will discuss upcoming challenges
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2026-1-29 19:13
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
霍州市| 子长县| 池州市| 灵台县| 海门市| 连山| 孟津县| 洪江市| 株洲市| 定南县| 吴江市| 凤山县| 乌拉特中旗| 东兰县| 高陵县| 漳浦县| 玛多县| 法库县| 沁阳市| 吴堡县| 东乡| 平顶山市| 南投市| 扬州市| 罗平县| 嘉义县| 赤城县| 屏南县| 龙岩市| 西乌珠穆沁旗| 肇源县| 胶南市| 京山县| 宁远县| 津市市| 呼玛县| 东山县| 正蓝旗| 尚义县| 同仁县| 万全县|