POMDP与MDP的区别？部分可观测如何理解？ - 知乎
对比Belief MDP和普通MDP的贝尔曼最优方程中，可以发现，核心的区别在于Belief MDP里是对观测量求和，MDP则是对状态量求和。 在MDP里面，当前状态是确定的，动作也是确定的，但是下一步的状 …
What is the difference between Reinforcement Learning(RL) and …
May 17, 2020 · What is the difference between a Reinforcement Learning (RL) and a Markov Decision Process (MDP)? I believed I understood the principles of both, but now when I need to compare the …
machine learning - From Markov Decision Process (MDP) to Semi …
Jun 20, 2016 · Markov Decision Process (MDP) is a mathematical formulation of decision making. An agent is the decision maker. In the reinforcement learning framework, he is the learner or the …
为什么一般强化学习要建模成Markov Decision Process（MDP）？有什 …
8 个回答 默认排序 中原一点红 个人理解，希望可以多多交流： 简单结论：MDP是用于形式化 序列决策问题 的一个框架，而强化学习可以理解为是用于求解MDP或者它的扩展形式的一类方法，所以强化 …
Real-life examples of Markov Decision Processes
Apr 9, 2015 · I haven't come across any lists as of yet. The most common one I see is chess. Can it be used to predict things? If so what types of things? Can it find patterns amoung infinite amounts of …
强化学习中q learning和MDP的区别是什么？ - 知乎
强化学习求解TSP（一）：Qlearning求解旅行商问题TSP（提供Python代码） - 知乎 (zhihu.com) 一、Qlearning简介 Q-learning是一种强化学习算法，用于解决基于奖励的决策问题。它是一种无模型的 …
Why is the optimal policy in Markov Decision Process (MDP), …
Jan 10, 2015 · 0 In my opinion, any policy that achieves the optimal value is an optimal policy. Since the optimal value function for a given MDP is unique, this optimal value function actually defines a …
Whats exactly deterministic and non deterministic in deterministic and ...
Feb 11, 2021 · Q1. But I was guessing can MDP also specify probabilities with which a1 and a2 are followed from S3. If answer to Q1 is yes, then Q2. What deterministic policy will specify, fixed action …
强化学习中连续时间马尔可夫过程的MDP是如何处理的？ - 知乎
Aug 31, 2019 · 知乎讨论强化学习中连续时间马尔可夫过程的MDP处理方法，分享知识与见解。
mdp中部分状态变量的转移与动作无关，而与环境自身的某些随机因素 …
在这篇发表于ICLR-19的文章中，作者认为一个exogenous, stochastic input process将控制这种不受决策影响的变量。但是这个process可能并非是Markov的，因此不能直接把这种变量看作state的一部分， …