2018 Fiscal Year Annual Research Report
The Establishment of Evolutionary Knowledge Management for Societal and Organizational Optimization
| Project/Area Number |
17F17308
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| Research Institution | The University of Tokyo |
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Principal Investigator |
チン ユ 東京大学, 大学院新領域創成科学研究科, 教授 (00272394)
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| Co-Investigator(Kenkyū-buntansha) |
GU JIE 東京大学, 新領域創成科学研究科, 外国人特別研究員
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| Project Period (FY) |
2017-10-13 – 2020-03-31
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| Keywords | agent-based modeling / behavioral experiment / knowledge management / complexity and evolution / risk and uncertainty |
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| Outline of Annual Research Achievements |
The ultimate goal is to establish a new field of study on evolutionary knowledge management (KM) with the advancement of agent-based modeling (ABM) and behavioral experiments. Several model extensions were implemented, e.g.one on KM under turbulent and stable environment, one with monetary and social incentives and dilemmas, and one on KM impact to the macroeconomic outcomes. With deep understanding of human agents' independent and interdependent behavior from the empirical experiments, computer agents were modeled in the simulation emulating the human reality. Then, large scale and long term results were produced by the ABM which also exhibit the inter-temporal dynamics of the social interactions. With enhancement of the simulation, practical and effective administrative policy for optimization can be suggested and tested.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
Although the research project involves intensive labor and computer effort, the output has been delivered as planned, which includs a book chapter of Advances in Intelligent Systems and Computing on Springer publisher, a conference paper in the Proceedings of IKMAP2018, a poster and oral presentation at 9th International Conference on Complex Systems, a conference paper in the Proceedings of JSAI2019. Not only in academia, several industry-collaborated projects are also carried out. A side project on developing an Agent-Based Model of Tokenomics with X-order Lab in Shanghai, and a project on cryptocurrency ecology with a wealth management in HK, and a stakeholder conflict resolution ABM with KTH university Sweden. These efforts will also extend academic value of complex system simulation.
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| Strategy for Future Research Activity |
Much future work is to be done. First is to improve, re-evaluate, deepen and consolidate the developed agent-based model. Hence, further theory and inside can be derived. Also, some system exhibited phenomena are not yet elucidated, such as phase transition and boundary conditions. Therefore, when doing the econophsical analysis, model revision or recheck the computing codes are needed. The integration of ABM and behavioral experiments is advantageous but difficult. Human vs. Computer agents' decision-making needs to be further explored. Additionally, many ongoing work needs to be published as journal papers. The research execution has been carried out smoothly, but the paper publication has been relatively slow. Hence, the productivity of publication needs to be improved as well.
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