A Multiagent Reinforcement Learning Solution for Geometric Configuration Optimization in Passive Location Systems
نویسندگان
چکیده
منابع مشابه
Transfer Learning for Multiagent Reinforcement Learning Systems
Reinforcement learning methods have successfully been applied to build autonomous agents that solve many sequential decision making problems. However, agents need a long time to learn a suitable policy, specially when multiple autonomous agents are in the environment. This research aims to propose a Transfer Learning (TL) framework to accelerate learning by exploiting two knowledge sources: (i)...
متن کاملCoordination in multiagent reinforcement learning systems by virtual reinforcement signals
This paper presents a novel method for on-line coordination in multiagent reinforcement learning systems. In this method a reinforcement-learning agent learns to select its action estimating system dynamics in terms of both the natural reward for task achievement and the virtual reward for cooperation. The virtual reward for cooperation is ascertained dynamically by a coordinating agent who est...
متن کاملA .net Reinforcement Learning Platform for Multiagent Systems
Reinforcement learning is a convenient way of allowing the agents to autonomously explore and learn the best action sequences that maximize their overall value, based on successive rewards received from the environment. Among other similar libraries and platforms, the reinforcement platform presented here is especially designed to be used with the .NET framework and provides a general support f...
متن کاملMultiagent Reinforcement Learning for Multi-Robot Systems: A Survey
Multiagent reinforcement learning for multirobot systems is a challenging issue in both robotics and artificial intelligence. With the ever increasing interests in theoretical researches and practical applications, currently there have been a lot of efforts towards providing some solutions to this challenge. However, there are still many difficulties in scaling up the multiagent reinforcement l...
متن کاملA multiagent architecture for concurrent reinforcement learning
In this paper we propose a multiagent architecture for implementing concurrent reinforcement learning, an approach where several agents, sharing the same environment, perceptions and actions, work towards one only objective: learning a single value function. We present encouraging experimental results derived from the initial phase of our research on the combination of concurrent reinforcement ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Mathematical Problems in Engineering
سال: 2021
ISSN: 1563-5147,1024-123X
DOI: 10.1155/2021/6691254