The Military Strategy Threat of Cognitive System Based on Agent

Yang, Tiejian; Min-le, Wang; Fang, Maoyan

doi:10.1007/978-3-642-33030-8_119

Cited by 1 publication

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“…Cooperative multiagent and multirobot teams are promising in the domain of distributed artificial intelligence, such as controlling of a large number of unmanned aerial vehicles [1], coordinating soldiers, agents and robots in battlefield [2], and searching and rescuing in disasters [3]. In those teams, agents work together toward their common goal, and similar to the infrastructure of human society, they only closely coordinate with a few teammates either logically or under the constraints of physical communications, with a peer-topeer associate network structure.…”

Section: Introductionmentioning

confidence: 99%

Reorganizing Complex Network to Improve Large-Scale Multiagent Teamwork

Liu

2014

Mathematical Problems in Engineering

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Large-scale multiagent teamwork has been popular in various domains. Similar to human society infrastructure, agents only coordinate with some of the others, with a peer-to-peer complex network structure. Their organization has been proven as a key factor to influence their performance. To expedite team performance, we have analyzed that there are three key factors. First, complex network effects may be able to promote team performance. Second, coordination interactions coming from their sources are always trying to be routed to capable agents. Although they could be transferred across the network via different paths, their sources and sinks depend on the intrinsic nature of the team which is irrelevant to the network connections. In addition, the agents involved in the same plan often form a subteam and communicate with each other more frequently. Therefore, if the interactions between agents can be statistically recorded, we are able to set up an integrated network adjustment algorithm by combining the three key factors. Based on our abstracted teamwork simulations and the coordination statistics, we implemented the adaptive reorganization algorithm. The experimental results briefly support our design that the reorganized network is more capable of coordinating heterogeneous agents.

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Section: Introductionmentioning

confidence: 99%

Reorganizing Complex Network to Improve Large-Scale Multiagent Teamwork

Liu

2014

Mathematical Problems in Engineering

View full text Add to dashboard Cite

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The Military Strategy Threat of Cognitive System Based on Agent

Cited by 1 publication

References 2 publications

Reorganizing Complex Network to Improve Large-Scale Multiagent Teamwork

Reorganizing Complex Network to Improve Large-Scale Multiagent Teamwork

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