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Integrating individual and social intelligence into module-based agents without central coordinator

机译:将个人和社会智能整合到基于模块的代理商,没有中央协调员

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Robots are complex entities that can be modeled as multi-agent systems. The multi-agent paradigm provides an integrated intelligence framework such as a path planning agent that uses search techniques interacts with a fuzzy-based agent that moves the robot to a given location. Agent coordination is required to achieve the appropriate global behavior. When there is no central agent that coordinates the overall architecture, the intelligence required for social interaction should therefore be deployed at the agent level. In such a situation, individual intelligence (how to reach a goal) and social intelligence (how to collaborate or compete for resource with other agents) should be integrated at the agent level. In this paper we propose the use of module-based agents to achieve this integration. The whole multi-agent robot architecture, ARMADiCo, has been implemented with several module-based agents and tested on a Pioneer 2DX of ActivMedia. Some preliminary results are shown and discussed.
机译:机器人是复杂的实体,可以建模为多代理系统。多代理范例提供了一个集成的智能框架,例如使用搜索技术与基于模糊的代理商交互的路径规划代理,该代理将机器人移动到给定位置。代理协调是达到适当的全局行为所必需的。当没有坐标整体架构的中央代理时,因此应在代理级别部署社交交互所需的智能。在这种情况下,个人情报(如何达到目标)和社会智能(如何与其他代理商合作或竞争资源),应在代理层面上集成。在本文中,我们建议使用基于模块的代理来实现这种集成。整个多代理机器人架构armadico已经使用了多个基于模块的代理实现并在Activedia的Pioneer 2DX上进行了测试。显示并讨论了一些初步结果。

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