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Social simulation is a research field that applies computational methods to study issues in the social sciences. The issues explored include problems in computational law , psychology , [ 1 ] organizational behavior , [ 2 ] sociology , political science, economics , anthropology, geography, engineering , [ 2 ] archaeology and linguistics ...
Agent-based social simulation (or ABSS) [1] [2] consists of social simulations that are based on agent-based modeling, and implemented using artificial agent technologies. Agent-based social simulation is a scientific discipline concerned with simulation of social phenomena , using computer-based multiagent models.
Recent work on the Modeling and simulation of Complex Adaptive Systems has demonstrated the need for combining agent-based and complex network based models. [ 21 ] [ 22 ] [ 23 ] describe a framework consisting of four levels of developing models of complex adaptive systems described using several example multidisciplinary case studies:
Model-driven approach focuses on model building and finding universal laws which govern human behavior in societies, for example social simulations or social physics. Digital society-focused approach , where computational social scientists seek to address problems emerging in algorithmic society, such as algorithmic bias .
Swarm is an open-source agent-based modeling simulation package, useful for simulating the interaction of agents (social or biological) and their emergent collective behavior. Swarm was initially developed at the Santa Fe Institute in the mid-1990s, and since 1999 has been maintained by the non-profit Swarm Development Group.
Human-in-the-loop simulation of outer space Visualization of a direct numerical simulation model. Historically, simulations used in different fields developed largely independently, but 20th-century studies of systems theory and cybernetics combined with spreading use of computers across all those fields have led to some unification and a more systematic view of the concept.
In the last few years, the agent-based modeling (ABM) community has developed several practical agent based modeling toolkits that enable individuals to develop agent-based applications. More and more such toolkits are coming into existence, and each toolkit has a variety of characteristics.
Latent space models (Sarkar and Moore, 2005) [3] and agent-based simulation are often used to examine dynamic social networks (Carley et al., 2009). [4] From a computer simulation perspective, nodes in DNA are like atoms in quantum theory, nodes can be, though need not be, treated as probabilistic.