Collective decision making plays an increasingly important role everywhere in today?s human society. Existing literature addresses issues in collective decision making with linear statistical analysis or relatively simple dynamical modeling. Either approach is still limited in capturing the complexity of real human decision making dynamics that typically involve high-dimensional nonlinear problem space, nontrivial societal structure, within-individual cognitive and behavioral patterns, and/or between-individual diversity. In this project the PIs will develop a novel conceptual/computational multi-level model of the dynamics of complex collective decision making by shifting the viewpoint from the dynamics of participants to the dynamics of ideas being discussed. Collective decision making will be redefined as evolution of ecologies of ideas over a social network habitat, where populations of potential solutions evolve via continual applications of evolutionary operators such as reproduction, recombination, mutation, selection, and migration of solutions, each conducted by participating humans. The effects of various model as-sumptions on collective decision making will be studied through computer simulations, and their results will be evaluated through experiments of team decision making on complex collaborative tasks with human subjects. This project will generate a novel perspective on human and social dynamics by introducing evolutionary principles and methodologies into the modeling of their complex behaviors, making a theoretical advancement from a traditional, individually-focused psychological or social science paradigm to a more dynamic, multilevel, evolutionary paradigm for collective social processes. A number of practical implications will be produced, e.g., the effects of coherence of shared information and organizational structure within teams upon their exploratory and adaptive performances, which will be widely applicable to current issues that many human organizations are facing today. The outcomes of this project will be integrated into undergraduate and graduate education at Binghamton University.
