In the third chapter differential games theory based on Q-learning was designed.
在第三章设计了基于Q -学习的微分对策方法。
This paper is concerned with the problem of a novel Q-learning algorithm for solving optimal cost function.
该文利用求解最优费用函数的方法给出了一种新的Q学习算法。
Readers'collision problem was analyzed and an anti-collision algorithm based on Q-learning was presented out in the paper.
文章分析了读卡器碰撞的两种情形，提出了基于Q学习的仿碰撞算法，并进行了仿真测试。
Q-learning was applied to resolution of the adaptive dispatching rule selection problem under dynamic single-machine scheduling environment.
提出了一种利用Q-学习解决动态单机调度环境下的自适应调度规则选择的方法。
Trying to improve the learning time, the reward values in Q-learning method are not constant. MFQLA tuned the reward values according to current state.
为了改善学习的时间，Q学习方法中的奖励值并不是固定的，而是根据状态而变化。
For reinforcement learning control in continuous Spaces, a Q-learning method based on a self-organizing fuzzy RBF (radial basis function) network is proposed.
针对连续空间下的强化学习控制问题，提出了一种基于自组织模糊rbf网络的Q学习方法。
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.
学习是一种典型的强化学习，其学习效率较低，尤其是当状态空间和决策空间较大时。
I analyze the request of curriculum arrangement, using intellect learning arithmetic's Q-learning, designing an applied mathematics model to deal with this problem.
本文对大学课表的排课要求进行了全面的分析，结合智能学习算法的Q学习算法，设计出了课表编排问题的较为实用的模型。
The reinforcement learning is adopted to control and decision for AUV, and Q-learning, BP neural net, artificial potential is integrated to avoidance planning for AUV.
主要采用强化学习的方法对AUV进行控制和决策，综合Q学习算法、BP神经网络和人工势场法对AUV进行避碰规划。
A single behavior object contains the algorithm for optimizing the demonstrated group of ACTS. The algorithm is using the Q-learning based on artificial nerve network.
在单独的行为对象中包含了基于强化学习中的Q学习及人工神经网络的优化学习算法。
In order to enhance the study speed and the convergence rate of Q-learning algorithm, an algorithm that based on the experience knowledge about environment is proposed.
为了提高智能体系统中的典型的强化学习——Q -学习的学习速度和收敛速度，使学习过程充分利用环境信息，本文提出了一种基于经验知识的Q -学习算法。
The result of simulation illustrates that the signal control method based on Q-Learning is better than fixed-time control, actuated control and signal control based on genetic algorithms.
仿真实验的结果表明，基于Q -学习的信号控制方法优于定时控制、感应式控制和基于遗传算法的信号控制方法。
In order to reduce the delay of cars passing through intersections, control strategies are set up by cloud model and some parameters of the control model are improved by Q-learning method.
为了减少车辆通过路口的延误，采用云模型建立控制策略，运用Q -学习改进控制模型的参数。
Then the four main algorithms including dynamic programming, monte carlo method, temporal-difference and Q-learning are given respectively, and their difference and relation are pointed out.
动态规划、蒙特卡罗算法、时序差分算法、Q-学习，并指出了它们之间的区别和联系。
A new model based on Markov decision processes is proposed and the correlative novel algorithm is implemented with the adaptive ability of improved Q-learning for dynamic grid service selection.
对满足马尔可夫决策过程的服务组合提出了一种支持不完备信息描述的网格服务描述模型，实现了对服务组合整个生命周期的描述。
This sample graph is from a simple reinforcement learning application that USES Q learning.
这个示例图是从使用Q学习的一个简单增强式学习应用程序中得到的。
Q school mission: to help more people enjoy learning to inspire potentiality, reveal goodness, and realize their dreams.
问学堂使命：帮助更多人享受学习，激发潜能，彰显美善，实现梦想。
A fuzzy Q learning algorithm is proposed in this dissertation, which map continuous state Spaces to continuous action Spaces by fuzzy inference system and then learn a rule base.
首先，提出一种模糊Q学习算法，通过模糊推理系统将连续的状态空间映射到连续的动作空间，然后通过学习得到一个完整的规则库。
Research on local path planning of mobile robot based on Q reinforcement learning and CMAC neural networks.
基于Q强化学习与CMAC神经网络的移动机器人局部路径规划研究。
Combined with Q - learning, action tracing and intrusion forecasting, this model is applied to detect and response to the unknown intrusion.
该模型把Q -学习、行为意图跟踪和入侵预测结合起来，可获得未知入侵行为的检测和响应。
The agent has a high intelligence and can improve the learning ability according to the dynamic environment with the ability of Q learning.
学习使智能体具有较高的智能性，可以通过提高自己的学习能力适应不断变化的动态环境。
In this paper Q reinforcement learning algorithm is adopted for mobile robot local path planning. It makes mobile robot resolve the problem of local path planning in a complex environment.
将Q强化学习算法应用于移动机器人局部路径规划，解决了移动机器人在复杂环境中的局部路径规划问题。
Q. s. For them, learning comes too easily and they never find out how to buckle down.
对他们来说，学习是件轻而易举的事，因而他们从未想过如何全力以赴地学习。
Q learning method is used in intelligence planning path with magnets to achieve the shortest path search, obstacle avoidance, task scheduling and so on.
采用Q学习方法进行磁钉路径的智能规划，实现最短路径寻找，同时解决了任务调度及避障等问题。
The improved Q learning algorithm was suggested because of the traditional algorithm has limitations of slow and partial constringency.
传统的Q学习存在收敛速度慢和容易导致局部收敛的矛盾，为此提出一种改进的Q学习算法。
As the situation in the court gradually becomes complex, the learning rate of traditional Q learning will be slow and the interaction difficulty.
随着赛场上态势的渐趋复杂，传统的Q学习速度会变得很慢且交互困难。
The paper proposes a model of reinforcement learning based on ant colony algorithm, namely the combination of ant colony algorithm and Q learning.
本文提出了一种基于蚁群算法的强化学习模型，即蚁群算法与Q学习相结合的思想。
Q learning algorithm is the most popular reinforcement learning algorithm, but the algorithm exist some problems.
目前主流的强化学习算法是Q学习算法，但Q学习本身存在一些问题。
To solve the problem of slow update speed in Q learning, a multi-step Q learning scheduling algorithm is proposed, in which the value function is updated based on the information in multiple steps.
针对任务调度的Q学习算法更新速度慢的问题，提出一种基于多步信息更新值函数的多步q学习调度算法。
To solve the problem of slow update speed in Q learning, a multi-step Q learning scheduling algorithm is proposed, in which the value function is updated based on the information in multiple steps.
针对任务调度的Q学习算法更新速度慢的问题，提出一种基于多步信息更新值函数的多步q学习调度算法。
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