自主计算的共生认知计算视角

J. Kephart, J. Lenchner
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引用次数: 25

摘要

共生认知系统(SCS)是由人类和软件代理组成的多代理系统,旨在共同执行认知任务,如决策,比人类或软件代理在没有帮助的情况下做得更好。自主计算系统(ACS)是多代理系统,它根据管理员和用户指定的目标管理应用程序以及软件和硬件资源。SCS和ACS有一些共同的关键特征。首先,两者都是为了扩展人类的智力能力而设计的,因此它们需要有效的手段,使人类能够将他们的目标传达给计算系统。其次,它们的自然架构是一个多代理系统,其中有数十个、数百个甚至更多的半自治实体相互作用。在SCS和ACS中,主体间的沟通和协调问题都是突出的。我们报告了我们使用中等规模的SCS原型的经验,该原型可以帮助人类专家做出财务影响范围从数百万美元到数十亿美元的公司合并和收购决策。利用共性,我们将这一经验转化为可能有利于未来ACS研究的见解,并建议更关注代理-人类通信和构建现实的系统原型。
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A Symbiotic Cognitive Computing Perspective on Autonomic Computing
Symbiotic Cognitive Systems (SCS) are multi-agent systems comprising both human and software agents that are designed to collectively perform cognitive tasks such as decision-making better than humans or software agents can unaided. Autonomic Computing Systems (ACS) are multi-agent systems that manage applications as well as software and hardware resources in accordance with goals specified by human administrators and users. SCS and ACS share some key characteristics. First, both are designed to extend human intellectual capabilities, and as such they require effective means by which humans can communicate their objectives to the computing system. Second, their natural architecture is a multi-agent system in which dozens, hundreds or even more semi-autonomous entities interact. In both SCS and ACS, issues of inter-agent communication and coordination come to the fore. We report our experience with a moderate-scale SCS prototype that helps human experts make decisions with financial impacts ranging from millions to even billions of US: corporate mergers and acquisitions. Taking advantage of the commonalities, we translate this experience into insights that may benefit future research on ACS, and recommend a stronger focus on agent-human communication and building realistic system prototypes.
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