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- W3134737341 abstract "Many social sciences such as psychology and economics try to learn the behaviour of complex agents such as humans, organisations and countries. The current statistical methods used for learning this behaviour try to infer generally valid behaviour, but can only learn from one type of study at a time. Furthermore, only data from carefully designed studies can be used, as the phenomenon of interest has to be isolated and confounding factors accounted for. These restrictions limit the robustness and accuracy of insights that can be gained from social/economic systems. Here we present the online platform TreeOfKnowledge which implements a new methodology specifically designed for learning complex behaviours from complex systems: agent-based behaviour learning. With agent-based behaviour learning it is possible to gain more accurate and robust insights as it does not have the restriction of conventional statistics. It learns agent behaviour from many heterogenous datasets and can learn from these datasets even if the phenomenon of interest is not directly observed, but appears deep within complex systems. This new methodology shows how the internet and advances in computational power allow for more accurate and powerful mathematical models." @default.
- W3134737341 created "2021-03-15" @default.
- W3134737341 creator A5056918900 @default.
- W3134737341 date "2021-02-27" @default.
- W3134737341 modified "2023-09-27" @default.
- W3134737341 title "Tree of Knowledge: an Online Platform for Learning the Behaviour of Complex Systems." @default.
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