Abstract
Much attention has been paid on exploring the solutions for cooperative dilemma in multi-agent systems. Thereinto, the evolutionary game theory which describes cooperative dilemma is seen as an effective approach. Notably, many of previous works are based on the ideal hypothesis that individuals can feasibly obtain their neighbours’ payoffs to update strategies. Considering the difficulty of getting the exact information about payoffs, we propose the switching probabilities between strategies which do not require the payoffs. Here the evolutionary dynamics driven by the switching probabilities in a three-strategy game model is established. Results show that the steady state of the gaming system is closely related with the switching probability matrix. These findings give a novel account about the decision making process in the gaming systems, when a strategy updating rule weakening the ideal assumption about payoffs is established.
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Acknowledgements
We acknowledge the financial support from the National Natural Science Foundation of China (Grant Nos. 61603199 and 61603201 and 61573199).
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Xu, Z., Zhang, J., Li, Q., Chen, Z. (2018). Decision Making in Multi-agent Systems Based on the Evolutionary Game with Switching Probabilities. In: Jia, Y., Du, J., Zhang, W. (eds) Proceedings of 2017 Chinese Intelligent Systems Conference. CISC 2017. Lecture Notes in Electrical Engineering, vol 459. Springer, Singapore. https://doi.org/10.1007/978-981-10-6496-8_12
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DOI: https://doi.org/10.1007/978-981-10-6496-8_12
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