Computing norm´s benefit awareness via norm adoption ratio and norm morality

One of the issues of norm adoption is identifying which norms fit a visitor agent. The agent, equipped with a norm detection algorithm, detects the norms that are practiced by local agents. The agent usually detects the strong norms and ignore the weak ones. However, we propose a novel concept of norm adoption by computing the norms benefits for the agent. To increase its utility, the agent adopts the norms that return considerable benefits to itself. It does this by computing the factors that constitute its awareness of the norms´ benefits. Previously, we identified Norm Adoption Ratio, Norm Morality, Norm Yield and Norm Trust as these factors. In this paper, we compute the first two factors which are Norm Adoption Ratio and Norm Morality. We employ a Norm Strength formula to compute the Norm Adoption Ratio and propose a new architecture to compute the Norm Morality.