Strategy evaluation and optimization with an artificial society toward a Pareto optimum
Overview of the proposed universal computational experiment framework for strategy evaluation and optimization in a fine-grained artificial society
Strategy evaluation and optimization in response to troubling urban issues has become a challenging issue due to increasing social uncertainty, unreliable predictions, and poor decision-making. To address this problem, we propose a universal computational experiment framework with a fine-grained artificial society that is integrated with data-based models. The purpose of the framework is to evaluate the consequences of various combinations of strategies geared towards reaching a Pareto optimum with regards to efficacy versus costs.
