Emergence measurement of robot swarm intelligence based on swarm entropy

Pu FENG; Wenjun WU; Jie LUO; Xin YU; Yongkai TIAN

doi:10.11959/j.issn.2096-6652.202213

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Emergence measurement of robot swarm intelligence based on swarm entropy

Special Topic: Crowd Intelligence | 更新时间：2024-06-05

- Emergence measurement of robot swarm intelligence based on swarm entropy
- Chinese Journal of Intelligent Science and Technology Vol. 4, Issue 1, Pages: 65-74(2022)
- 作者机构：
  
  1. 北京航空航天大学计算机学院，北京 100191
  2. 北京航空航天大学人工智能研究院，北京 100191
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-6652.202213
  CLC： TP181
- Published Online：2022-03，
  
  Published：15 March 2022
- 稿件说明：
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Pu FENG, Wenjun WU, Jie LUO, et al. Emergence measurement of robot swarm intelligence based on swarm entropy[J]. Chinese journal of intelligent science and technology, 2022, 4(1): 65-74.
DOI：

Pu FENG, Wenjun WU, Jie LUO, et al. Emergence measurement of robot swarm intelligence based on swarm entropy[J]. Chinese journal of intelligent science and technology, 2022, 4(1): 65-74. DOI： 10.11959/j.issn.2096-6652.202213.

摘要

群体行为往往能产生远超个体行为的价值和复杂度。为了在个体智能的基础上更有效地衍生出群体智能，需要基于群体熵来科学地衡量群体智能水平，并以群体熵为引导目标，推动群体智能的增强和演进。针对这个重要的科学问题，以无人小车群体为研究对象，提出基于参数共享和群体策略熵的多智能体soft Q learning算法，通过共享智能体的观测信息，并结合最大熵强化学习方法，实现探索型任务中群体策略的持续学习更新。同时，通过将群体熵定义为度量工具，刻画群体学习中熵变化模式，实现对群智汇聚过程的定量分析。

Abstract

Swarm behavior can often produce value and complexity far beyond individual behavior.In order to more effectively derive swarm intelligence on the basis of individual intelligence

it is necessary to scientifically measure the level of swarm intelligence based on swarm entropy

and use swarm entropy as the guiding goal to promote the enhancement and evolution of swarm intelligence.Aiming at this important scientific problem

the unmanned car group as the research object was taken and a multi-agent soft Q learning method based on parameter sharing and group strategy entropy was proposed.Which by sharing the observation information of the agent

combined with the maximum entropy reinforcement learning method

to achieve continuous learning and updating of swarm strategies in exploratory tasks.At the same time

by defining swarm entropy as a measurement tool

characterizing the entropy change pattern in swarm learning

realizing the quantitative analysis of the gathering process of swarm intelligence.

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references

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