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Q_learning
- 强化学习是人工智能中策略学习的一种，基于预期最大利益原则。和博弈论有密切的关系，也是多主体系统学习的常用方法。-Reinforcement learning is a kind of artificial intelligence in the strategic study, based on the principle of best interests is expected. And game theory are closely related, but also multi-agen
RL_Learning
- 详细的讲述强化学习中Q学习算法，并且应用在区域交通系统中，是适合初学者。-RL—learning,q_learning,transform system,for beginner
Q_learning
- 使用html5实现q_learnning算法-use html5 achieve q_learning algorithm
Q_learning
- Q learning for reinforcement learning
questiong one
- Q_learning的简单matlab教程(The visual paradigm of matlab.)
Q_learning
- q学习,强化学习中的人工智能方法，实用型强化学习(Q learning, reinforcement of artificial intelligence methods, practical reinforcement learning)
Q_learning
- Q学习的经典实例，入门经典教程程序，实例对应的是从任一房间出发，走出去的最优路径(classic examples of Q-learning, getting started classic tutorial program)
Q_learning
- 强化学习代码，求解贝尔曼方程，用qlearning求解(Reinforcement learning code, behrman equation, using qlearning solution)
Q_learning
- 这是一种简单的网格迷宫问题Q-learning实现(This is a simple Q-learning implementation of grid maze problem)