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23 August 2022 The differences between VDN and COMA algorithms in PyMARL and implications for their win rate in different SMAC scenarios
Jiajun Song
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Proceedings Volume 12305, International Symposium on Artificial Intelligence Control and Application Technology (AICAT 2022); 1230516 (2022) https://doi.org/10.1117/12.2645632
Event: International Symposium on Artificial Intelligence Control and Application Technology (AICAT 2022), 2022, Hangzhou, China
Abstract
In the current SMAC paper, almost no one has analyzed the reason of the difference of success rate% between PyMARL algorithms used in SMAC. The purpose of this article is to study the code differences and the idea differences between VDN algorithm and COMA algorithm in PyMARL framework used in SMAC environment, and the influence of these two algorithms on the result of SMAC experiment. The conclusion of this paper is that VDN algorithm is superior to COMA algorithm in SMAC. Because in almost all scenarios of SMAC, the algorithm based on value function (VDN) can solve simple cases very quickly and effectively, while the algorithm based on strategy gradient (COMA) converges to local minimum easily, and it is extremely difficult for COMA to come up with a perfect strategy.
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Jiajun Song "The differences between VDN and COMA algorithms in PyMARL and implications for their win rate in different SMAC scenarios", Proc. SPIE 12305, International Symposium on Artificial Intelligence Control and Application Technology (AICAT 2022), 1230516 (23 August 2022); https://doi.org/10.1117/12.2645632
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KEYWORDS
Detection and tracking algorithms
Optimization (mathematics)
Systems modeling
Algorithms
Data modeling
Expectation maximization algorithms
Machine learning
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