Aim of the workshop

The recent explosion of online big data has allowed us to conduct high-resolution quantitative modeling and analysis of complex human social behaviors. This has completely changed the way of studying collective behaviors of humans in social systems. Conventional approaches that attempted to model human behaviors using mathematically rigorous yet idealized game theoretic frameworks often failed to predict real social dynamics, because humans are often irrational and do not follow well-defined decision making protocols. Big data analytics provides us with more empirical methods and tools to capture and analyze such realistic human behaviors. 

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Meanwhile, this change does not necessarily mean the traditional theoretical frameworks such as game theory have lost values in scientific research on human behaviors. What is more important than ever, is to merge and integrate these multiple approaches to develop a comprehensive methodology for the understanding of human social behaviors. The key ingredient that transcends methodological variations is “computation.”

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The aim of this workshop is to provide a transdisciplinary venue where researchers within and outside the Artificial Life community can come together, share their cutting-edge research on data-driven approaches and/or theoretical/mathematical approaches to human social behaviors, and collectively develop an integrated, comprehensive computational methodology for the understanding of real-world human social dynamics. Of particular interest at this workshop, as an example of hybrids of multiple approaches, is in the hybrid coordination of autonomous software agents and real humans, which has a potential to show better performance in practical problem solving than only humans or software alone. Other computational and/or hybrid approaches will also be explored. The topics of interest at this workshop include (but are not limited to):

 

• Social dynamics

• Social coordination

• Social simulation

• Social networks

• (Evolutionary) game theory

• Collective intelligence

• Collective dynamics

• Experimental economics

• Network experiments

• Economic games

• Online labor markets

• Online social data sets

• Software agents

• Computational social science

• Hybrid approaches