Studying Collective Human Decision Making and Creativity with Evolutionary Computation
This work addresses the problem of modeling and analyzing collective human dynamics for researchers in computational, organizational, and social sciences, though it appears incremental in applying existing EC concepts to a new context.
The researchers tackled the problem of understanding collective human decision making and creativity by redefining them as the evolution of ecologies of ideas, using evolutionary computation as a framework, simulation model, and research tool, and tested hypotheses through experiments with real human subjects, demonstrating EC's potential for interdisciplinary research.
We report a summary of our interdisciplinary research project "Evolutionary Perspective on Collective Decision Making" that was conducted through close collaboration between computational, organizational and social scientists at Binghamton University. We redefined collective human decision making and creativity as evolution of ecologies of ideas, where populations of ideas evolve via continual applications of evolutionary operators such as reproduction, recombination, mutation, selection, and migration of ideas, each conducted by participating humans. Based on this evolutionary perspective, we generated hypotheses about collective human decision making using agent-based computer simulations. The hypotheses were then tested through several experiments with real human subjects. Throughout this project, we utilized evolutionary computation (EC) in non-traditional ways---(1) as a theoretical framework for reinterpreting the dynamics of idea generation and selection, (2) as a computational simulation model of collective human decision making processes, and (3) as a research tool for collecting high-resolution experimental data of actual collaborative design and decision making from human subjects. We believe our work demonstrates untapped potential of EC for interdisciplinary research involving human and social dynamics.