1) Double Deep Q-Network (DDQN):DDQN有一个Q网络和一个具有相同架构的目标Q网络。在视觉编码层之后,网络之后是5个密集层,隐藏层范围从256到32个节点。输出大小等于可能动作的数量,每个动作代表对应动作的Q值。网络使用Adam优化器进行训练,学习率为10-3。 2) Twin Delayed Deep Deterministic Policy Gradient (T...
深度强化学习(Deep Reinforcement Learning, DRL)则让算法通过在智能体(agent)采取的每一个动作(action)时提供一个奖励(reward)信号来进行自我学习,因此不会受到分布不匹配的影响。这个奖励可以是稀疏的,并不能准确描述智能体应该做什么,而只是描述所采取的行动在局部的好坏。智能体的最终目标是使累积的奖励总和最大化...
Model-free即没有对环境的知识,不对环境建模,与model-based相对。 model-free部分的算法大致可以分为三个部分:policy optimization,Q-learning以及两者的结合。 几个基本的Model-free算法分类 [论文]Model-free 论文整理 Playing Atari with Deep Reinforcement Learning NIPS Deep Learning Workshop 2013 |paper Volodym...
最近组里在讨论接下来在强化学习这块的研究方向,在讨论之前,我们把强化学习各个子方向的论文都粗略过了一下,涉及到model-free/model-based/multi-agent/deep exploration/meta-learning/imitation learning/application/distributed training等方向。我想着当时查找阅读相关文章花费了不少精力,决定开个专栏把我看的论文给整理...
This survey presents an overview of the current model-free deep reinforcement learning landscape. It provides a comparison of state-of-the-art on-policy and off-policy algorithms in the value-based and policy-based domain. Influences and possible drawbacks of different algorithmic approaches are ...
The model-free approaches to control of neural systems presented here suggest that deep reinforcement learning has potential for application to this area. We show how the engineering problem is transformed from one that focuses on the design of appropriate system dynamics and the control of these m...
“Model-based methods rely on planning as their primary component, while model-free methods primarily rely on learning.” Sutton& Barto, Reinforcement Learning: An Introduction In the context of reinforcement learning (RL), the model allows inferences to be made about the environment. For example,...
不大确定我理解了问题，不知道actor critic 算法里用supervised learning来update critic，用policy gradient...
Sample-Efficient Deep Reinforcement Learning for Continuous Control and Temporal Difference Models (TDM), interpreting a parameterized Q-function as a generalized dynamics model for novel temporally abstracted model-based planni... S Gu 被引量: 0发表: 2018年 MODEL-FREE INTELLIGENT CONTROL USING REINFO...
1. 中医是否符合端到端学习和模型自由深度强化学习（RL）？端到端学习：端到端学习通常指通过深度学习...