Behavioural Rehearsing Illuminates Scientific Problems of Organised Complexity
arxiv(2024)
摘要
As artificial intelligence becomes increasingly prevalent in scientific
research, data-driven methodologies appear to overshadow traditional methods in
resolving scientific problems. In this Perspective, we revisit a classic
classification of scientific problems and rethink the evolution of scientific
paradigms from the standpoint of data, algorithms, and computational power. We
observe that the strengths of new paradigms have expanded the range of
resolvable scientific problems, but the continued advancement of data,
algorithms, and computational power is unlikely to bring a new paradigm. To
tackle unresolved problems of organised complexity in more intricate systems,
we argue that the integration of paradigms is a promising approach.
Consequently, we propose behavioural rehearsing, checking what will happen in
such systems through multiple times of simulation. One of the methodologies to
realise it, sophisticated behavioural simulation (SBS), represents a higher
level of paradigms integration based on foundational models to simulate complex
social systems involving sophisticated human strategies and behaviours. SBS
extends beyond the capabilities of traditional agent-based modelling simulation
(ABMS), and therefore, makes behavioural rehearsing a potential solution to
problems of organised complexity in complex human systems.
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