Agent based models of social systems and collective intelligence

Agent-based modeling and simulation techniques have now become a suitable and popularly used approach to build useful models of social systems, which not only helps to get better understanding of various social phenomena but also enriches the agent-based computing paradigm in return. Agent-based models allow simulating social units such as individuals, households, organizations or nations and their direct or indirect interactions. These models demonstrate how global order and collective intelligence can emerge from relatively simple local interactions and can explain the dynamics of the emergent behaviour. The agent-based modeling approach has provided the bridging link between psychological & sociological analysis of individual and social behaviours respectively, which was otherwise missing. This generative, proof-by-construction approach has also complemented the individual-centered research in cognitive science by showing that individual alone is not the crucial unit of cognition but is affected by environment and society besides affecting them as well. In this paper, we have given an analytical account of agent-based modeling of emergent collective social behaviours, on these lines, along with relevant theoretical & experimental outcomes and their implications for multi-agent systems.