Observational learning is a typical component

In this CP 690550 manner, we can obtain the threshold of the t-tht-th decision maker and the probability of the t-tht-th decision maker’s choice after observing the decisions made by the previous decision makers. These possibilities are shown in Table 1.
Table 1.
    Possible outcomes of the decision task.ttth decision maker’s identificationAA better (aa)Waiting (ww)BB better (bb)RealityAA better (μAμA)p(a μA,At)=∫r(β)+ε+∞p(s μA)dsp(w μA,At)=∫r(β)-εr(β)+εp(s μA)dsp(b μA,At)=∫-∞r(β)-εp(s μA)dsBB better (μBμB)p(a μB,At)=∫r(β)+ε+∞p(s μB)dsp(w μB,At)=∫r(β)-εr(β)+εp(s μB)dsp(b μB,At)=∫-∞r(β)-εp(s μB)dsFull-size tableTable optionsView in workspaceDownload as CSV
In the G-WB model, we employ the G-WB criterion where the key is biochemistry the threshold r(β)r(β) and we find the iterative relationship between βtβt and βt+1βt+1. Thus, decision makers’ actions are determined by their private signals and previous decisions in sequence.