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What do you think is the single most influential factor in determining with whom you become friends and whom you form romantic relationships? You might be surprised to learn that the answer is simple: the people with whom you have the most contact. This most important factor is proximity. You are more likely to be friends with people you have regular contact with. For example, there are decades of research that shows that you are more likely to become friends with people who live in your dorm,...
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Communication between two animals occurs when one animal transmits an information signal that causes a change in the animal that receives the information. Organisms communicate with one another in a host of different ways. Signals can be auditory, chemical, visual, tactile, or a combination of these. Communication is a critical behavioral adaptation that promotes survival, growth, and reproduction.
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The barriers to effective communication also include cultural barriers, semantic barriers, gender barriers, and time constraints.
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Neurons, the fundamental units of the brain and nervous system, communicate through complex electrochemical signals that underpin all cognitive and bodily functions. This communication is primarily facilitated by a process involving the generation and propagation of an action potential along the axon of the neuron. When the internal electrical charge of a neuron surpasses a certain threshold, an action potential is triggered. This rapid change in voltage travels swiftly along the axon to the...
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通过通信互补图增强异构多代理系统的协作.

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    科学领域:

    • 人工智能的人工智能
    • 多代理系统 多代理系统
    • 强化学习是一种强化学习.

    背景情况:

    • 异质的多剂体系统具有不同的任务和有限的剂体观测.
    • 参数共享在同质系统中是有效的,但在异质系统中却是昂贵的.
    • 现有的方法在异质的多代理合作中难以应对勘探成本.

    研究的目的:

    • 提出一种新的通信互补图模型 (CCGM),以加强在异质多代理系统中的协作.
    • 为了应对这些系统中有限的观测和高的勘探成本的挑战.
    • 为了提高异质代理强化学习 (HARL) 算法的性能.

    主要方法:

    • 在HARL框架内开发了一种通信辅助图形模型 (CCGM).
    • 利用的优势函数分解和政策趋同的连续更新.
    • 引入了一种灵感来自于信号游戏的通信方法,通过图表模块将信息与观察结果对齐.

    主要成果:

    • CCGM有效地增强了在异构的多代理系统中的协作.
    • 该模型在多剂粒子环境 (MPE) 中表现出更好的性能.
    • 多剂型MuJoCo (MAMuJoCo) 机器人实验中的评估证实了CCGM的有效性.

    结论:

    • CCGM提供了一种新的解决方案,用于在异质的多代理系统中进行通信.
    • 拟议的模型成功地减轻了与有限的观测相关的勘探成本.
    • 在复杂的场景中,CCGM显著提高了基于HARL的算法的能力.