Modeling Collective Behavior for Fish School With Deep Q-Networks

Author:

Chen Pengyu1ORCID,Wang Fang1,Liu Shuo1,Yu Yifan1,Yue Shengzhi1,Song Yanan1,Lin Yuanshan1ORCID

Affiliation:

1. College of Information Engineering, Dalian Ocean University, Dalian, China

Funder

National Natural Science Foundation of China

Liaoning Province Natural Science Foundation

Foundation of Liaoning Educational Committee

Liaoning Key Research and Development Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Reference37 articles.

1. Simple Model for Active Nematics: Quasi-Long-Range Order and Giant Fluctuations

2. Emergent escape-based flocking behavior using multi-agent reinforcement learning;hahn;arXiv 1905 04077,2019

3. Phase Transitions in Systems of Self-Propelled Agents and Related Network Models

4. Automated discovery of local rules for desired collective-level behavior through reinforcement learning;costa;Frontiers in Physiology,2020

5. Intrinsic and extrinsic noise effects on phase transitions of network models with applications to swarming systems

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