Sophisticated Behavioral Simulation

As artificial intelligence becomes increasingly prevalent in scientific research, data-driven methodologies appear to overshadow traditional methods in resolving scientific problems. 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 organized complexity in more intricate systems, we argue that the integration of paradigms is a promising approach. Consequently, we propose behavioral rehearsing, checking what will happen in such systems through multiple times of simulation. One of the methodologies to realize it, sophisticated behavioral simulation (SBS), represents a higher level of paradigm integration based on foundational models to simulate complex social systems involving sophisticated human strategies and behaviors. SBS extends beyond the capabilities of traditional agent-based modeling simulation (ABMS) and, therefore, makes behavioral rehearsing a potential solution to problems of organized complexity in complex human systems.