Pattern-oriented inverse simulation for agent-based modeling

Abstract

Pattern Oriented Modeling (POM) is an approach to bottom-up complex system analysis, which was developed in ecology and for agent-based complex systems. This paper proposes a pattern-oriented inverse simulation (PIS) to analyze agent-based complex systems. We apply PIS to a history simulation domain, which aims to analyze a particular family line with more successful candidates in the civil service examination in imperial China. Two relevant patterns observed in the real family system are employed to decode family strategies along such an elite family line. We implement PIS through inverse simulation techniques, by fitting the simulated results to the real genealogical data arranged in time-series as patterns. Intensive experiments show a practical applicability of PIS in agent-based complex systems.