搜索资源列表
qianguazhi6
- jiangjie强化学习的原理，通过仿真更能理解什么是强化学习(Jiangjie the principle of strengthening learning, through simulation, more understanding of what is intensive learning)
最优控制
- 此程序利用强化学习的方法实现小车的最优控制。(Optimal control of car)
RL
- 用python搭建了各类常用的强化学习算法的框架，通过迷宫寻路的例子实现各类算法。(The fr a mework of all kinds of commonly used reinforcement learning algorithms is built with Python, and all kinds of algorithms are realized by the example of labyrinth finding
c_netwebhxbc
- .NET编程源码，以供学习参考查阅。强化学习效果(.NET programming source for learning reference.)
reforce
- 强化学习的Q学习，关于强化学习的应用和算法，有很好的思路，可以从中举一反三，从而解决自己的问题，希望对大家能有所帮助(To strengthen the study of Q learning and to strengthen the application and algorithm of learning, we have a good idea. We can take one counter three from the mi
tf-adnet-tracking-master
- 基于强化学习深度学习用于单目标跟踪算法的源码(Based on reinforcement learning, deep learning is used for single target tracking algorithm.)
qlearning4k-master
- qlearning4k是强化学习Python深度学习lib库Keras插件。它简单，是快速成型的理想选择。(Qlearning4k is a reinforcement learning add-on for the python deep learning library Keras. Its simple, and is ideal for rapid prototyping.)
蒙特卡罗算法与matlab(精品教程)
- 蒙特卡洛算法也常用于机器学习，特别是强化学习的算法中。一般情况下，针对得到的样本数据集建立相对模糊的模型，通过蒙特卡洛方法对于模型中的参数进行选取，使之于原始数据的残差尽可能的小。从而达到建立模型拟合样本的目的。(Monte Carlo algorithm is also commonly used in machine learning, especially in reinforcement learning algorithm.
ddpg
- 深度强化学习中DDPG算法的代码，用Python语言实现(The code of DDPG algorithm in deep reinforcement learning, implemented in Python language)
DDPG-Keras-Torcs-master
- 基于keras框架的强化学习代码，主要实现的是DDPG算法的代码，用keras框架实现(Reinforced learning code based on keras fr a mework)
code
- Q-learning 算法实现AGV的最优路径规划，实测效果非常好，对于研究深度学习和强化学习的同学很有帮助！(The Q-learning algorithm realizes the optimal path planning of AGV, and the measured results are very good. It is very helpful for students who are studying deep le
MAgent-master
- 多智能体的一段代码，有关强化学习，机器学习，很实用的一段代码！(A code of multi-agent, about reinforcement learning, machine learning, a very practical piece of code!)
mtncarMatlab
- 强化学习qlearning编写，回归算法规划轨迹(Reinforcement learning qlearning, return algorithm to plan trajectory)
10_7_gridworld_sarsa
- 通过最基础的实例来了解sarsa算法原理及应用(Understand the principle and application of sarsa algorithm through the most basic example.)
RL
- 强化学习 DQN代码，和通信相关，利用python进行训练，大家可以看看(reinforcement learning)
pytorch-a2c-ppo-acktr-master
- 改代码为ACKTR代码，该算法比传统的TRPO和DQN在运行速度和计算量都有很大的提升(scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation)
单一任务导航
- 测试深度马尔可夫决策来导航,给出了python的实现代码(MDP based navigation)
Q_Learning
- 实现强化学习交通配时，选取最优的配时方案(To realize the reinforcement learning traffic timing, the optimal timing scheme is selected)
qlearning
- 利用栅格法建模，基于强化学习Qlearning算法实现路径规划，可以实时显示(Using raster method to model and Qlearning algorithm based on reinforcement learning to realize path planning, it can be displayed in real time.)
Python核心编程入门必备强化葵花宝典
- python入门教学，案例示范，语言学习(python for beginners)