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A Distributed Swarm Intelligence System

A swarm intelligence and distributed technology, applied in transmission systems, resource allocation, multi-programming devices, etc., can solve problems such as insufficient data sets

Active Publication Date: 2022-03-25
王静逸
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0016] (4) Multi-agent game and training evolution to solve the problem of insufficient data sets

Method used

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  • A Distributed Swarm Intelligence System
  • A Distributed Swarm Intelligence System
  • A Distributed Swarm Intelligence System

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0095] like Figure 15 As shown, this architecture belongs to a typical HLA architecture, in which the federation 1 computing center 1 and the federation 2 computing center 2 are the federation center nodes of the two federations respectively; in the federation 1, the organizational computing unit 1 and the organizational computing unit 2 belong to Federation members, cameras belong to objects as an entity computing unit, and each distributed intelligent node is connected and interacted with each other by installing this system. The system uses different surveillance cameras to form its own small network, and then combines the network to form a larger organizational network. The combination of organizational network and centralized cloud platform can give full play to the computing power of the camera. The system identifies tasks through parallel computing, shares machine learning models, video encoding and decoding computing resources, and shared data through networking, and...

Embodiment 2

[0099] like Figure 16 As shown, this is a typical DDS model, a flat terrain environment, coordination of multi-entity (multi-person, multi-vehicle, etc.) calculations, including AI simulation, AI coordination (traffic coordination) and other means of architecture.

[0100] The architecture divides the entire terrain into 4 areas. Different areas publish different DDS topics. The computing platform unit of each area is the topic, and the non-stop entity computing unit is the publisher or subscriber. The related computing entities (vehicles) can be The theme of the region, synchronization of distributed data, model calculation.

[0101] Further, because the distributed intelligent system also supports other systems, distributed group AI decision-making can also be realized through the synchronization and parallel computing of the distributed intelligent system and other topics.

Embodiment 3

[0103] In the distributed swarm intelligence system, through the combination of the software development kit (SDK) and the computing layer of the agent, the coordinated operation of multiple computing entities and agents is supported, and the information of computing models and data is shared through distributed intelligent nodes as Multi-Agents. routing channel.

[0104] The distributed swarm intelligence system will support the asynchronous computing and data synchronization mechanism between tensorflow and agents, support distributed machine learning, and achieve a collaboration mechanism between multiple agents. The specific distributed machine learning system structure diagram, such as Figure 17 shown:

[0105] Among the commonly used machine learning algorithm categories, such as inductive learning, analogical learning, reinforcement learning, analytical learning, genetic algorithm, etc., each algorithm is processed by an agent, and through the way of distributed model...

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Abstract

A distributed swarm intelligence system, including: the underlying protocol layer, which is used to apply network protocols; the core software platform layer, which is used to call computing resources of external system platforms, and supports distributed systems, consensus algorithms and computing models; and open software The layer is used to provide an open source system framework; the distributed system includes at least one or more of: HLA system, DDS system, and Multi-Agent system. The invention solves the problems of large-scale calculation, splitting of calculation models, collaboration of multi-intelligent expert systems, group intelligent decision-making, flexible organization of intelligent system decision-making and the like.

Description

technical field [0001] The patent of the present invention relates to the field of computer distributed systems, in particular to the field of distributed artificial intelligence group decision-making systems under different distributed systems. Background technique [0002] In recent years, artificial intelligence has made great progress with the breakthrough of neural network, especially in the fields of image, analysis, recommendation and so on. With the rapid development of artificial intelligence, problems such as the continuous expansion of computing scale, the too single expert system, the flexibility of neural network models and the complexity of application fields are also constantly escalating. In such an environment, the development of distributed artificial intelligence has been put on the agenda by research institutions and large enterprises. The existing more popular distributed systems mainly include the following three. [0003] 1. The distributed solution ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L67/10H04L67/1042H04L67/1095H04L67/56G06F9/50H04L69/16
CPCH04L67/10H04L67/1059H04L67/1095G06F9/5083H04L69/162H04L67/56
Inventor 王静逸
Owner 王静逸