1.1 off-policy定义 强化学习中的off-policy方法采用两个策略,一个用来学习并最终成为最优策略,另一个具有试探性,用来产生智能体的行为样本。用来学习的策略被称为目标策略,用于生成样本的策略被称为行为策略。在这种情况下,我们认为学习所用的数据“离开”了待学习的目标策略,因此整个过程被称为off-policy(离轨策略...
off-policy evaluation 评估Off-Policy Evaluation(OPE)是一种用于评估强化学习中的策略的方法,它利用行为策略采样的数据来评估目标策略的价值函数。OPE的目标是估计一个给定的目标策略的价值函数,从而了解该策略的性能。 OPE可以通过多种方法进行,其中包括Direct Method Estimator(DM)、Inverse Propensity Scoring(IPS)和...
讲两篇 off-policy evaluation 相关的工作,组会上面讲到。 原文传送门 Voloshin C, Le H M, Jiang N, et al. Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning[J]. arXiv preprint arXiv:1911.06854, 2019. Thomas P S, Theocharous G, Ghavamzadeh M. High-confidence off-p...
off-policy评估是强化学习领域中的一种重要技术，它允许我们在不需要使用目标策略直接采样数据的情况下，对策略进行评估。这一方法通常涉及到两个策略：目标策略和行为策略。目标策略用于评估，而行为策略则用于产生数据。在off-policy评估过程中，我们面临的主要挑战包括部分可观测性问题和反事实推理。部分可观...
摘要:先前的大多数 Offline-RL 方法都采用了涉及 Off-policy evaluation 的迭代 Actor-Critic (AC) 方法。本文中我们证明了只需简单地基于 behavior policy 的 on-policy 。这种 One-step 算法在大部分 D4RL benchmark 上击败了之前的迭代算法。这种 One-step baseline 在实现强大性能的同时,比以前提出的迭代算...
Monte Carlo(MC) Off Policy Evaluation 目标:在给定由行为策略π 2 \pi_2π2产生的轮次(episodes)下,评估策略π 1 \pi_1π1的价值V π ( s ) V^\pi(s)Vπ(s) s 1 , a 1 , r 1 , s 2 , a 2 , r 2 , . . . . s_1,a_1,r_1,s_2,a_2,r_2,...s1,a1...
This leads us to examine off-policy policy evaluation (OPE) in such settings. We focus on OPE for value-based methods, which are of particular interest in deep RL, with applications like robotics, where off-policy algorithms based on Q-function estimation can often attain better sample ...
(e.g., a ranking) based on some context–a common scenario in web search, ads, and recommendation. We build on techniques from combinatorial bandits to introduce a new practical estimator that uses logged data to estimate a policy’s performance. A thorough empirical evaluation on real-world ...
We build on techniques from combinatorial bandits to introduce a new practical estimator that uses logged data to estimate a policy's performance. A thorough empirical evaluation on real-world data reveals that our estimator is accurate in a variety of settings, including as a subroutine in a ...
Such off-policy evaluation methods, which estimate the performance of a policy using trajectories collected from the execution of other policies, heretofore have not provided confidences regarding the accuracy of their estimates. In this paper we propose an off-policy method for computing a lower ...