Reward Constrained Policy Optimization Tessler, Chen, Daniel J. Mankowitz, and Shie Mannor. "Reward constrained policy optimization." arXiv preprint arXiv:1805.11074 (2018). 亮点 本文不仅支持以discounted sum表示的约束,也支持mean value constraints,即这种形式的约束: E[(∑tTct)/T]≤α 本工作是re...
Policy gradientActor-criticThe PPO (Proximal Policy Optimization) algorithm is a policy optimization-based deep reinforcement learning algorithm that has achieved outstanding results and widespread applications. Despite the popularity of the PPO algorithm, it has several notable drawbacks, including its ...
A Unified Pairwise Framework for RLHF: Bridging Generative Reward Modeling and Policy Optimization 场景设定: 一个高科技研究设施的会议室。与会的专家包括:AI先驱和理论家艾伦·图灵博士(Dr. Alan Turin…
Achiam J, Held D, Tamar A, et al (2017) Constrained policy optimization. In: International conference on machine learning, PMLR, pp 22–31 Akrour R, Schoenauer M, Sebag M (2011) Preference-based policy learning. In: Machine Learning and Knowledge Discovery in Databases: European Conference...
policy.py feat: init Oct 26, 2023 requirements.txt feat: init Oct 26, 2023 train.py feat: init Oct 26, 2023 README MIT license Official implementation ofDirect Preference-based Policy Optimization without Reward Modeling, NeurIPS 2023.
This is the soucre code of the model-based offline reinforcement learning method Conservative Reward for model-based Offline Policy optimization (CROP).InstallationInstall MuJoCo 2.1.0 Create a conda environment for CROP.conda env create -f CROP.yml conda activate CROP Usage...
作者应该好好调整 backbone policy optimization algorithms,让 performance 与原始论文中的结果匹配。回答:就是很难复现那些结果,并且虽然有的 performance 低了,但也有 performance 高了。并且,我们的 main contribution 不是刷榜,而是 offline apprenticeship learning setting。
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Honglak Lee, Mehdi Fatemi 2021 International Conference on Machine Learning|May 2021 Publication We propose the k-Shortest-Path (k-SP) c...
We consider constrained Markov decision processes (MDP's) with compact state and action spaces under long-run average reward or cost criteria, and give the characterization of an optimal pair of initial state distribution and policy, which maximize over all policies the essential infimum of the ...
However, such a constrained surge-pricing strategy may fail to balance demand and supply in certain cases—e.g., even adopting the highest allowed price cannot reduce peak-period demand to a level at which the market clears without some form of non-price rationing. To address this limitation,...