offline model-based RL算法会受到model OOD的影响(model在有限的数据集上过拟合,在测试时会产生外推误差)。本文没有将策略探索约束在in-support的区域,而是直接探究在out-of-support区域的行为决策能力,提出的方法为MAPLE 由于策略的约束,之前的方法往往考虑如何尽可能利用offline dataset并将价值函数限制在行为策略的...
但是这些结果中,与现有的model-free和model-based相比,COMBO在不同类型数据集中普遍表现良好,这表明COMBO对不同的数据集类型具有鲁棒性编辑于 2023-02-01 20:16・IP 属地四川 内容所属专栏 Model Based RL(MBRL) model-based RL Algorithms 订阅专栏 Offline RL 离线强化学习 订阅专栏...
【这个题目确实有点蹭热点了\~\~\~】 Motivation 本文想将dreamer结构结合到meta-RL中,因为dreamer利用的RSSM结构能够处理POMDP问题,因此将其直接运用于meta-RL中适应于context-based meta-RL中任务信息是部分可观测的情况。本文依据前文的理论,将高维的任务分布分… ...
A Taxonomy of Model-Based RL Algorithms We’ll start this section with a disclaimer: it’s really quite hard to draw an accurate, all-encompassing taxonomy of algorithms in the Model-Based RL space, because the modularity of algorithms is not well-represented by a tree structure. So we will...
在这种情况下,选择有效的 model-free algorithms 使用更加合适的,特定任务的表示,以及 model-based algorithms 来用监督学习的方法来学习系统的模型,并且在该模型下进行策略的优化。利用特定任务的表示显著的改善了效率,但是限制了能够从更加广泛的 domain 知识上学习和掌握的任务的范围。利用 model-based RL 能够改善...
model based就是有一个world model可以用来做planning，而model free就是没有对env dynamics进行建模，...
In this paper, we introduce a novel algorithmic framework for designing and analyzing model-based RL algorithms with theoretical guarantees, and a practical algorithm Optimistic Lower Bounds Optimization (OLBO). In particular, we derive a theoretical guarantee of monotone improvement for model-based RL...
The proposed training framework can be extended to more control actions with more sophisticated trainer design to further reduce the tweak cost of model-based RL algorithms. 展开 关键词: Computer Science - Machine Learning DOI: 10.48550/arXiv.1805.09496 年份: 2018 ...
Model-based whole-body control of such robots, can generate complex dynamic behaviors through the simultaneous ex... Tsagarakis,Ng,G Sinclair,... 被引量: 0发表: 2017年 加载更多来源会议 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, & Brain 26 September 2013 研究点...
Our model-based approach works with both on-policy or off-policy RL algorithms. We further design the back-testing and execution en- gine which interact with the RL agent in real time. Using historical real financial market data, we simulate trading with practical constraints, and demonstrate ...