Chinese Journal of Intelligent Science and Technology ›› 2022, Vol. 4 ›› Issue (1): 65-74.doi: 10.11959/j.issn.2096-6652.202213

• Special Topic: Crowd Intelligence • Previous Articles     Next Articles

Emergence measurement of robot swarm intelligence based on swarm entropy

Pu FENG1, Wenjun WU2, Jie LUO1, Xin YU1, Yongkai TIAN1   

  1. 1 School of Computer Science and Engineering, Beihang University, Beijing 100191, China
    2 Institute of Artificial Intelligence, Beihang University, Beijing 100191, China
  • Revised:2022-01-19 Online:2022-03-15 Published:2022-03-01
  • Supported by:
    Science and Technology Innovation 2030 — “New Generation Artificial Intelligence” Major Project(2018AAA0102300)


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.

Key words: swarm entropy, swarm intelligence, deep reinforcement learning

CLC Number: 

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