本文是从learning from demonstration的角度减缓MARL算法中sample efficiency的问题,常见的方式只有一个demonstrator,本文则采用多个demonstrator(expertise in distinct aspects of the environment)从而提高学习的效果 Q2这是否是一个新的问题?reinforcement learning from demonstration 14年就被提出了,比较经典的方法是Q ...
Gang Chen,Zhonghua Yang,Hao He,Kiah Mok Goh.Coordinating Multiple Agents via Reinforcement Learning[J]. Autonomous Agents and Multi - Agent Systems .2005(3)G. Chen, Z. Yang, H. He, and K. M. Goh, "Coordinating multiple agents via reinforcement learning," Autonom. Agents and Multi-Agent ...
A multi-agent reinforcement learning approach to obtaining dynamic control policies for stochastic lot scheduling problem This paper presents a methodology that, for the problem of scheduling of a single server on multiple products, finds a dynamic control policy via intellige... CD Paternina-Arboleda...
6) multi agent reinforcement learning 多智能体增强学习 补充资料:增强体 分子式:CAS号:性质:为复合材料中承受载荷的组分。按几何形状来分,增强体有零维的颗粒状、一维的纤维状、二维的片状和三维的立体结构。按属性来分则有无机和有机增强体,其中有合成的也有天然的。主要的增强体是纤维状的,如无机的玻璃纤维、...
In this paper we revise Reinforcement Learning and adaptiveness in Multi-Agent Systems from an Evolutionary Game Theoretic perspective. More precisely we ... K Tuyls,A Nowe,T Lenaerts,... - 《Synthese》 被引量: 26发表: 2004年 Discrete Double Auctions with Artificial Adaptive Agents: A Case ...
and further the impact on different AUs varies as the environmental condition changes. We then present Elixir, a system to enhance the video stream quality for multiple analytics on a video stream. Elixir leverages Multi-Objective Reinforcement Learning (MORL), where the RL agent caters to the ob...
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability Many real-world tasks involve multiple agents with partial observability and limited communication. Learning is challenging in these settings due to local ... S Omidshafiei,J Pazis,C Amato,... 被引量: 69发...
When I run a single agent in each job, the application works correctly. However, when I try to run more than one agent in the same job (same node), the application hangs. I do not think the problem is the application itself because it works when there is a single...
Paper tables with annotated results for SOC-Boundary and Battery Aging Aware Hierarchical Coordination of Multiple EV Aggregates Among Multi-stakeholders with Multi-Agent Constrained Deep Reinforcement Learning
For this example you create two reinforcement learning agents. Both agents operate at the same sample time in this example. Set the sample time value (in seconds). Get Ts = 0.1; When you create the agent, the initial parameters of the critic network are initialized with random values. Fix...