这一思路源自自然语言处理中的Transformer模型,通过将过去的序列信息输入模型,预测未来的动作。该方法的代表作是决策Transformer(Decision Transformer, DT),它将离线强化学习转化为一个有监督学习问题,通过历史状态、动作和回报的序列来预测最优的未来动作。虽然CSM方法在某些任务中表现优异,但它在面对次优数据拼接(stitchi...
通常来讲,环境是很复杂的,智能体的下一状态可能带有一定的随机性(比如当你失去一个球发射另一个球时,它的方向是随机的)。 马尔可夫决策过程; Markov decision process 一系列的状态、动作、以及采取动作的规则构成了一个马尔科夫决策过程(Markov decision process)。一个马尔科夫决策过程(比如一局游戏)由一串有限个...
Transformer encoderIn the burgeoning field of autonomous driving, reinforcement learning (RL) has gained prominence for its adaptability and intelligent decision-making. However, conventional RL methods face challenges in efficiently extracting relevant features from high-dimensional inputs and maximizing the...
Finance.A Q-learning-based training model can build models for decision-making assistance, such as determining optimal moments to buy or sell assets. Gaming.Q-learning models can train gaming systems to achieve an expert level of proficiency in playing a wide range of games as the model learns...
AlphaStar 神经网络结构将 Transformer 框架运用于模型单元(类似于关系深度强化学习),结合一个深度 LSTM 核心、一个带有 pointer network 的自回归策略前端和一个集中的值基线。超强的网络设计使得其适合长期序列建模和大输出空间(如翻译、语言建模和视觉表示)的挑战。它还还集成了多智能体学习算法。
Compared with Markov Decision Processes (MDP), agents in POMDP cannot fully receive information from the environment, which is an obstacle to traditional RL algorithms. One solution is to establishes a sequence-to-sequence model. As the core of deep Q-networks, Transformer has achieved certain ...
N-step Sarsa 是一种 On-policy 算法,但也可以借助重要度采样比改造为 Off-policy 形式。标准 N-step Sarsa 是对 Sarsa 的一个改进,二者仅在 TD target 时展开的步数方面有区别,用回溯图来看会更清晰 可见标准 Sarsa 仅展开了一步,所以它也可称为 1-step Sarsa,n-step Sarsa 是对它的推广。如图可见,我...
To address real world decision problems in reinforcement learning, it is common to train a policy in a simulator first for safety. Unfortunately, the sim-real gap hinders effective simulation-to-real transfer without substantial training data. However, collecting real samples of complex tasks is oft...
在评估过程中,SQL与多种先进的离线强化学习(RL)方法进行了比较,包括BC(行为克隆),10%BC,BCQ(Batch Constrained Q-learning),DT(Decision Transformer),TD3+BC,One-step RL,CQL(Conservative Q-learning)和IQL(Implicit Q-Learning)。这些比较的结果显示,SQL在复杂的任务(如AntMaze和Kitchen)中表现优越,而在性能...
of learning.· Bellman introduced the optimal control problem known as Markovian decision processe...