Pattern-Oriented Modeling of Commons Dilemma Experiments

Experimental data from a spatially explicit dynamic commons dilemma experiment is used to empirically ground an agent-based model. Four distinct patterns are identified in the data. Two naïve models, random walk and greedy agents, do not match the patterns. A more comprehensive model is presented that explains how agents make movement and harvest decisions. Using pattern oriented modeling the parameter space is explored to identify the parameter combinations that meet the four identified patterns. Less than 0.1% of the parameter space meets all the patterns. The resulting model can be used to design future experiments.