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POMG algorithm for large-scale pursuit game with partial observation and no communication.

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Fuzzy self-organizing cooperative coevolution (FSC2) for multi-target self-organizing pursuit

Official code for the paper "Toward multi-target self-organizing pursuit in a partially observable Markov game", which has been submitted to Arxiv and journal for peer-review.

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Using the following to cite:

Sun, L., Chang, Y.C., Lyu, C., Shi, Y., Shi, Y. and Lin, C.T., 2022. Toward multi-target self-organizing pursuit in a partially observable Markov game. arXiv preprint arXiv:2206.12330.

Description

In the proposed FSC2, the multi-target self-organizing pursuit (MTSOP or SOP) problem is decomposed into three subtasks: fuzzy-based distributed task allocation (DTA), self-organizing search (SOS), and single-target pursuit (STP).

Dependencies tested on

Python 3.7.11

numpy 1.19.1

torch 1.10.2

mpi4py 3.1.3

To run the comparison code of ApeX-DQN, additional dependencies are:

tensorflow 1.15.0

ray 1.10.0

To run the comparison code of MADDPG, additional dependencies are:

https://github.com/openai/multiagent-particle-envs

All the dependencies are listed in the file environment_for_mtsop_fsc2.yml.

Acknowledgements:

The actor-critic codes are mostly from and modified based on

The ApeX-DQN codes for comparison are from

The MADDPG codes for comparison are from

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