reinforcement learning system 中文意思是什麼
reinforcement learning system
解釋
強化式學習系統- reinforcement : n. 1. 增強，加固；補強物，強化物；補給品。2. 增援，支援；〈pl. 〉增援部隊，援軍；救援艦。
- learning : n 學，學習；學問，學識；專門知識。 good at learning 善於學習。 a man of learning 學者。 New learn...
- system : n 1 體系，系統；分類法；組織；設備，裝置。2 方式；方法；作業方法。3 制度；主義。4 次序，規律。5 ...
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In the respect of neural networks control for non - linear and uncertain system, a review of some available control strategy is made. combining neural networks control and conventional control strategy supervised learning, no supervised learning and reinforcement learning neural networks self - studying and adaptive control systems for ship course control are proposed. the thesis studies particularly their characteristics
在非線性和不確定性系統的神經網路控制方面，論文總結了一些現有的神經網路自學習控制系統，然後將神經網路和常規控制（例如pid控制、自適應控制、內模控制等）結合起來，根據船舶操縱的特點，詳細研究和分析了有監督學習、無監督學習和再勵學習的船舶航向神經網路自學習型自適應控制系統。 -
In recent years, reinforcement learning has become one of the key research areas in artificial intelligence and machine learning and it has attracted many researchers in other fields including operations research, control theory and robotics. reinforcement learning is different from supervised learning in that no teacher signals are needed and a reinforcement learning system learns by interacting with the environment to maximize the evaluative feedback from the environment
增強學習與監督學習的不同之處在於，增強學習不要求給定各種狀態下的期望輸出即教師信號，而強調在與環境交互中的學習，以極大（或極小）化從環境獲得的評價性反饋信號為學習目標。 -
The soccer robot system is a dynamic environment with multiple obstacles. it is a problem of high complexity to perform path planning in such environments. the traditional methods are not efficient in such complex environments. in this paper, a self - learning method of robot navigation is proposed based on the reinforcement learning method and artificial potential field method
本論文將增強式學習演算法和人工勢場法相結合，提出狀態評價函數和勢場的對應關系，以及控制策略和勢場力方向的對應關系，通過機器人的自適應學習，來形成優化的人工勢場，使機器人能夠以最短路徑繞過障礙，到達目標。 -
An experimental research of the effects of self - reinforcement and students ' expectations on learning efficiency in the dynamic system
關于動力系統中自我強化和學生期待對學習效率影響的實驗研究 -
While, some algorithms of machine learning are introduced to get the intelligence of the individual of hfutagent which makes individual skills in the robocup. finally, we realize the multi - agent cooperation mechanism using the knoledge of soccer experts. in our system, a typical cooperation method in robocup called sbsp is used, and we explains how to use reinforcement learning method to reach the goal of local cooperation, and the offense and defense strategy system is build by decision - theoretic
在本文中，首先介紹了典型的agent結構和mas模型和模擬機器人足球的一些主要模型：設計了一個分層的agent結構? hfutagent ，通過機器學習演算法實現了agent的個體智能；最後結合足球領域專家的知識實現了agent間的協作，其中使用了robocup中一個典型的協作方法- sbsp ，設計了一個通過強化學習的方法來達到agent之間的局部協作，把基於效用的對策論方法引入了hfutteam的進攻體系和防守體系中。 -
By means of the proposed reinforcement learning algorithm and modified genetic algorithm, neural network controller whose weights are optimized could generate time series small perturbation signals to convert chaotic oscillations of chaotic systems into desired regular ones. the computer simulations on controlling henon map and logistic chaotic system have demonstrated the capacity of the presented strategy by suppressing lower periodic orbits such as period - 1 and period - 2. meanwhile, the periodic control methodology is utilized, the higher periods such as period - 4 can also be successfully directed to expected periodic orbits
該控制方法無需了解系統的動態特性和精確的數學模型，也不需監督學習所要求的訓練數據，通過增強學習訓練方式，採用改進遺傳演算法優化神經網路權系數，使之成為混沌控制器，便可產生控制混沌系統的時間序列小擾動信號，模擬實驗結果表明它不僅能有效鎮定混沌周期1 、 2等低周期軌道，而且在周期控制技術基礎上，也可成功將高周期混沌軌道（如周期4軌道）變成期望周期行為。 -
Prior knowledge based reinforcement learning system
基於先驗知識的強化學習系統 -
Reinforcement learning has been applied to single agent environment successfully. due to the theoretical limitation that it assumes that an environment is markovian, traditional reinforcement learning algorithms cannot be applied directly to multi - agent system
由於強化學習理論的限制，在多智能體系統中馬爾科夫過程模型不再適用，因此不能把強化學習直接用於多智能體的協作學習問題。
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