• 便于强化学习交朋友强烈意向

    For convenience of intensive study, he has an intense intention of making friend with me.

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  • 学习一种重要强化学习算法。

    Learning is of great importance in reinforcement learning.

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  • 监督学习强化学习区别什么

    What are the differences between supervised learning and reinforcement learning?

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  • 讨论平均准则控制马氏强化学习算法

    An average reward reinforcement learning algorithm for control Markov chains is presented.

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  • 解释一下什么是“强化学习技术吗?

    Can you explain the A. I. technique called reinforcement learning?

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  • 参加为期强化学习测试解决问题实验。

    They go through nine days of a tensui studying, testing, and problem solving.

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  • 10定律是适用此前进行9年的集中强化学习

    Turns out the rule holds: he'd had nine years of intensive study.

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  • 强化学习技术运用于游戏集中方法文献都有记载

    Several approaches applying reinforcement learning techniques to game playing have been described in the literature.

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  • 论文主要研究基于平均强化学习算法动态调度方法

    The thesis mainly focuses on the dynamic scheduling method based on the averaged rewards reinforcement learning algorithms.

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  • 文中基于性能理论证明平均奖赏强化学习逼近定理

    In this paper, the approximate theorem of average reward reinforcement learning is proven by means of the theory of performance potentials.

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  • 强化学习这种情况的常用技术更多传统情形下需要使用效用函数

    Reinforcement learning is a common technique for this scenario as well as the more traditional scenario of actually learning the utility function.

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  • 强化学习这种特性必然增加智能系统的困难性学习时间增长

    This characteristic of reinforcement learning must increase learning difficulty for intelligent system and learning time also grows up.

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  • 初、高级培训班满足学员选择方便学员系统强化学习

    The series training programs of junior, middle and senior classes can not only satisfy trainee's selection accordingly, but also facilitate their continued upgrading progress for legal English.

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  • 说明:模拟智能机器小车通过强化学习算法学习最优导航策略

    Simulation machine car through reinforcement learning algorithm, learning optimal navigation strategies.

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  • 传统强化学习算法只能解决离散状态空间动作空间的学习问题。

    Conventional reinforcement algorithms only deal with discrete state Spaces and discrete action Spaces.

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  • 基于Q强化学习CMAC神经网络移动机器人局部路径规划研究

    Research on local path planning of mobile robot based on Q reinforcement learning and CMAC neural networks.

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  • 莱昂强化学习中心约翰·马歇尔中学受的教育二者都洛杉矶

    Leo was educated at the Center for Enriched Studies and John Marshall High School, both in LA.

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  • 提出强化学习中的状态,来描述观测状态信息完整引起不确定性

    The state entropy is proposed for reinforcement learning as the measurement of the state's uncertainty caused by the incompletion of the observed information.

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  • 基于强化学习的多指手控制方法,方法反馈控制强化学习相结合。

    The former one is a new approach combining reinforcement learning with feedback control.

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  • 学习人类学习模拟,主要监督学习强化学习监督学习

    The learning of connectionism, which consists mainly of supervised learning, intensive learning and unsupervised learning, is modelled after the learning of human beings.

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  • 主要研究强化学习算法及其机器人足球比赛技术动作学习问题中的应用

    This paper discusses reinforcement learning(RL)algorithm and its application to technical action learning of soccer robot.

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  • 理论分析基础上提出协同博弈强化学习算法证明了算法的收敛性。

    On the basis of theoretical analysis, the cooperative game reinforcement learning method is proposed and its convergence is proved.

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  • 学习一种典型强化学习,其学习效率低,尤其是状态空间决策空间较大时。

    Q-learning is a typical Reinforcement Learning (RL) method with a slow convergence speed especially as the scales of the state space and action space increase.

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  • 水下机器人编队任务探讨分布式强化学习多机器人系统中的应用模式

    Taking formation problem of multiple underwater vehicles as an example, the application model of DRL in multi-robot systems is illustrated.

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  • 对于有吸收目标状态循环任务,比较合理方法采用基于平均报酬模型的强化学习

    It is rational to adopt the average reward reinforcement learning algorithms for solving the absorbing goal states cyclical tasks.

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  • 本文提出了基于过程奖赏优先扫除强化学习算法作为多机器人系统的冲突消解策略

    A reinforcement learning algorithm based on process reward and prioritized sweeping is presented as interference solving strategy.

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  • 基于马尔科夫过程强化学习作为在线学习方式,能够好地应用智能体环境中

    Reinforcement learning based on Markov decision process is a way of on-line learning, which can be applied to single agent environment.

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  • 基于马尔科夫过程强化学习作为在线学习方式,能够好地应用智能体环境中

    Reinforcement learning based on Markov decision process is a way of on-line learning, which can be applied to single agent environment.

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