代理目标的对齐 (Alignment of Agent Objectives): 这指的是多代理系统中所有代理的目标或奖励函数是否相互一致或对齐。当所有代理的目标完全对齐时,他们会合作以最大化共同的奖励。当目标不完全对齐或存在冲突时,代理可能会竞争或采取对抗行动。 均衡点 (Equilibrium Points): 在多代理学习和博弈论中,均衡点是一个...
De Schutter, Multi-agent reinforcement learning: An overview. In Innovations in Multi-Agent Systems and Applications, pp. 183-221, 2010, Springer Berlin Heidelberg.L. Buşoniu, R. Babuška, B. De Schutter, Multi-agent reinforcement learning: An overview, in: Innovations in Multi-Agent ...
总的来说,{\bf{solve}}^i返回第i个agent在某个平衡点的最优策略,而{\bf{eval}}^i计算的是在假定所有agent保持在同一个平衡点上的时候,第i个agent在这个平衡点中期望的长远奖励。 3.2.2 基于策略的方法 基于多智能体系统的组合性质,基于价值的方法存在维数诅咒问题(在4.1节有进一步解释)。这一特征使得基于...
Recent years have witnessed significant advances in reinforcement learning (RL), which has registered tremendous success in solving various sequential decision-making problems in machine learning. Most of the successful RL applications, e.g., the games o
A central challenge in the field is the formal statement of a multi-agent learning goal; this chapter reviews the learning goals proposed in the literature. The problem domains where multi-agent reinforcement learning techniques have been applied are briefly discussed. Several multi-agent reinforcement...
Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms 来自 arXiv.org 喜欢 0 阅读量: 1599 作者:K Zhang,Z Yang,T Baar 摘要: Recent years have witnessed significant advances in reinforcement learning (RL), which has registered great success in solving various sequential...
Multi-agent reinforcement learning for wall modeling In RL, the agent interacts with its environment by sampling its states (s), performing actions (a), and receiving rewards (r). At each time step, the agent performs the action and the system is advanced in time before the agent can obser...
Learn what multi-agent reinforcement learning is and some of the challenges it faces and overcomes. You will also learn what an agent is and how multi-agent systems can be both cooperative and adversarial. Be walked through a grid world example to highlight some of the benefits of both dece...
Multi-agent reinforcement learning and its application to role assignment of robot soccer多智能体强化学习及其在足球机器人角色分配中的应用 Robot soccer is a typical multi-agent system. The action selected by each robot player not only depends on the current field state, but is also impacted by.....
设计了一个新颖的图卷积协作MARL框架,该框架集成了(i)我们I2精心设计的信用分配机制,该机制有效地塑造了每个agent的奖励,以促进合作,(ii)我们基于统计的行动表示,应对可变的agent规模,(iii)从大规模城市道路网络中捕获有用空间特征的图形卷积运算。 PRELIMINARIES ...