Q-learning algorithm is employed to compute the maximum consensus region and implement the consensus protocol design. The algorithm runs only on a single agent rather than the intercommunicating MAS hence the unattainable initial admissible protocols are not required. A numerical example is given to illustrate the effectiveness ...
This tutorial introduces the concept of Q-learning through a simple but comprehensive numerical example. The example describes an agent which uses unsupervised training to learn about an unknown environment. You might also find it helpful to compare this example with the accompanying source code examp...
Q Learning Algorithm Numerical Example Another Q learning Example: Tower of Hanoi Q-Learning Solution for Tower of Hanoi Q Learning using Matlab Q Learning using MS Excel Practice make perfect Resources Click here to purchase the complete E-book of this tutorial Send your feedback ...
通过Q-Table就可以找到每个状态下的期望值最高的action,进而通过找到所有的最优action来最终得到最大的期望奖励。 An example of Q-table: 中间的每个Q(s, a)都代表一个实数值, 算法流程: 1. 首先随机初始化Q-table。 2. 然后根据当前的state和Q-table,使用epsilon-greedy的方法根据Q值选择action。 3. 执行...
Recommendation systems.Q-learning models can help optimize recommendation systems, such as advertising platforms. For example, an ad system that recommends products commonly bought together can be optimized based on what users select. Robotics.Q-learning models can help train robots to execute various ...
5.2.TheQ-Learning algorithm5.3.Off-policy vs On-policy5.4.An example6.Tips6.1.如何理解强化学习中的折扣率? 1. What is RL? A short recap? In RL, we build an agent that can make smart decisions. For instance, an agent that learns to play a video game. Or a trading agent that learns...
This code demonstrates the reinforcement learning (Q-learning) algorithm using an example of a maze in which a robot has to reach its destination by moving in the left, right, up and down directions only. At each step, based on the outcome of the robot action it is taught and re-taught...
Algorithm to find a number that meets a gt (greater than condition) the fastest I have to check for the tipping point that a number causes a type of overflow. If we assume for example that the overflow number is 98, then a very inefficient way of doing that would be to start at 1....
最基础的算法——Q-learning，根据ADEPT的学习规律（Analogy / Diagram / Example / Plain / Technical...
我们的论文有三个主要贡献:第一,我们取得并评价了一个Q-learning表示,能够在连续领域中进行有效的Q-learning;第二,我们评估了几个能够把学习到的模型包含进模型无关的Q-learning的选项,并表明在我们的连续控制任务中,它们都缺乏效率。第三,我们提出,联合局部线性模型和局部在策略想象推广,加速对模型无关的连续Q-le...