本文主要提出了两种用于多机器人系统的安全多智能体强化学习(Safe Multi-Agent Reinforcement Learning, Safe MARL)算法:Multi-Agent Constrained Policy Optimization (MACPO)和MAPPO-Lagrangian。这两种算法旨在解决多机器人系统中的协作控制问题,确保各个智能体在最大化奖励的同时满足安全约束。 1.安全多智能体强化学习...
为了降低整个学习过程中的样本复杂度,文中提出了一种 Adaptive Opponent-wise Rollout Policy Optimization (AORPO)算法。 Two Parts of Sample Complexity 论文的一个关键设定是多智能体之间是可通讯的,即在不知道对手策略的情况下,可以通过通讯协议知道对手在任何状态下采取的行动。 ego agent send a state to the...
A Proximal Dual Consensus ADMM Method for Multi-Agent Constrained Optimization This paper considers a convex optimization problem with a globally coupled linear equality constraint and local polyhedron constraints and develops efficie... Chang,Tsung-Hui - 《IEEE Transactions on Signal Processing》 被引量...
Model-Based Multi-agent Policy Optimization with Dynamic Dependence Modeling Hu, Biyang,Yu, Chao,Wu, Zifan - International Conference on Parallel & Distributed Computing: Applications & Technologies - 2022 - 被引量: 0 Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinfor...
Agents andmulti-agent systemshave been used to study and to simulate complex systems in different application domain where physical factor are present for energy minimizing, wherephysical objectstend to reach thelowest energy consumptionpossible within the physically constrained world. Furthermore, MAS hav...
(2) Reshape the batch in your custom model from (batch, data) to (batch, agent_id, data) for processing (i.e., do the grouping in the model only). You will need some way of figuring out the agent id for each batch entry. ...
Unmanned Aerial Vehicles (UAVs) play a vital role in various civil and military applications, and their importance and convenience are widely recognized. As a core task of the autonomous control system for UAVs, path planning and design aim to solve a complex constrained optimization problem: findi...
For comparison, we run our game theoretic planner (GTP) against a model predictive controller (MPC), where the agent only plans for its own trajectory while naively assuming the opponents will travel in a straight line along the track. Note that such MPC approaches are the state-of-the-art...
Multi-Step Policy Ensemble Optimization 本文进一步提出了一个简单的OPE算法,用于实现multi-step policy improvement。相较于之前的BPPO使用online的方式进行评估,本文更贴合offline RL的setting 更新方式如下:其中i代指ensemble中的第i个,而k代指迭代的次数(multi-step),r(\pi^i)=\frac{\pi^i(a|s)}{\pi^i...
“Multi-agent DRL framework” section. As shown in Fig.1, a set of cloud serversM={1,…,M}can provide offloading computing services for a set of IoT devicesN={1,…,N}. Without loss of generality, we assume each IoT devicen∈Nmaintains a computation-intensive task to be processed ...