Heuristic collective learning for efficient and robust emergence of social norms
In multiagent systems, social norms is a useful technique in regulating agents’ behaviors to achieve coordination or cooperation among agents. One important research question is to investigate how a desirable social norm can be evolved in a bottom-up manner through local interactions. In this paper,...
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| Main Authors: | , , , , |
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| 格式: | text |
| 語言: | English |
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Institutional Knowledge at Singapore Management University
2015
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| 在線閱讀: | https://ink.library.smu.edu.sg/sis_research/4948 https://ink.library.smu.edu.sg/context/sis_research/article/5951/viewcontent/AAMAS15.pdf |
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| 機構: | Singapore Management University |
| 語言: | English |
| 總結: | In multiagent systems, social norms is a useful technique in regulating agents’ behaviors to achieve coordination or cooperation among agents. One important research question is to investigate how a desirable social norm can be evolved in a bottom-up manner through local interactions. In this paper, we propose two novel learning strategies under the collective learning framework: collective learning EV-l and collective learning EV-g, to efficiently facilitate the emergence of social norms. Experimental results show that both learning strategies can support the emergence of desirable social norms more efficiently in a much broader range of multiagent interaction scenarios than previous work, and also are robust across different network topologies. |
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