求解路徑學習 的英文怎麼說

中文拼音 [qiújiělùjìngxuéxí]
求解路徑學習 英文
learning from solution path
  • 求 : Ⅰ動詞1 （請求; 要求） ask; beg; request; entreat; beseech : 求人幫忙 ask sb a favour; ask a favou...
  • 解 : 解動詞（解送） send under guard
  • 路 : 1 （道路） road; way; path 2 （路程） journey; distance 3 （途徑; 門路） way; means 4 （條理） se...
  • 徑 : Ⅰ名詞1 （狹窄的道路; 小路） footpath; path; track 2 （達到目的的方法） way; means 3 （直徑的簡稱...
  • 學 : Ⅰ動詞1 （學習） study; learn 2 （模仿） imitate; mimic Ⅱ名詞1 （學問） learning; knowledge 2 （學...
  • 路徑 : 1. （道路） way; route; trajectory; path; tail; travel2. （門路） method; ways and means
  1. Supported by the national natural science foundation of china ( nsfc ) 2, the research topic of this paper has been focused on reinforcement learning and its applications in mobile robot navigation. one part of the main contents in this paper is the generalization methods for reinforcement learning in solving markov decision problems with continuous states and actions. another part of the main contents is the applications of reinforcement learning methods in the optimization of the path tracking controllers and the autonomous navigation controllers for mobile robots

    本文在國家自然科學基金項目「增強學習泛化方法研究及其在移動機器人導航中的應用」的資助下，以增強學習及其在移動機器人導航控制中的應用為研究內容，重點研究了增強學習在求解連續狀態和行為空間markov決策問題時的泛化（ generalization ）方法，並針對移動機器人在未知環境中的自主導航和路徑跟蹤控制器的優化設計問題，研究了增強學習在上述領域中的應用。
  2. The essay widely observes features and problems of the pursuit of our country ' s new curriculum integration, in comparison with integrated curriculum ' s development path and implementation ( experiment ) in america and japan. in comparison with special curriculum, it makes a mid - cosmic and microcosmic research on the integrated currivulum ' s teaching features. it has an initial try to build the model of teaching of the " problem - based learning "

    本文通過與美國、日本的綜合課程的發展路徑與課程實施（實驗）的比較，宏觀審視我國新一輪課程綜合化追求的特徵及問題；進而通過與分科課程的比較，在中觀和微觀層面探析綜合課程的教學特徵，初步嘗試構建綜合課程的「基於問題解決學習」的教學模式。
  3. Based on the above analysis, the research topic of this paper has been focused on 5 parts as follows : 1 ) the algorithms and theory of temporal difference learning ; 2 ) gradient learning algorithms for solving markov decision problems with continuous state or action space ; 3 ) hybrid learning methods for solving markov decision problems ; 4 ) the applications of reinforcement learning in the path tracking problems of mobile robots ; 5 ) reactive navigation methods based on reinforcement learning for mobile robots in unknown environments

    在此基礎上，本文的研究工作主要從5個方面展開，即：時域差值學習演算法和理論；求解馬氏決策問題的梯度增強學習演算法；求解馬氏決策問題的進化-梯度混合學習演算法；增強學習在移動機器人路徑跟蹤控制器優化中的應用；基於增強學習的移動機器人反應式導航控制。
  4. When we solve irregular problem, a trial solution of the differential equation is written as a sum of two parts : a radial basis function network satisfies the boundary conditions and svr is trained for the inner points

    在求解不規則邊界邊值問題時，演算法基於兩種不同學習方法的協作：徑向基函數學習網路（簡稱rbf ）用以滿足邊值條件（ bc ' s ） ，支持向量機回歸用於逼近域內元素。
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