Thresholds of Behavioral Flexibility in Turbulent Environments for Individual and Group Success
Results
There are three central results . First , flexibility can lead to suboptimality , directly and indirectly . Second , environmental turbulence affects utility both in terms of the environment itself and the social environment . Third , there are disadvantages to flexibility that do not rely on costs to changing behavior .
First , I present results from the base cases of the model .
Results from Base Cases
I
first present outcomes of the model in an unchanging environment . Recall that v can take on values 0 , 1 , and 2 . Table 2 shows the average outcomes over 30 runs for each vision environment when there are an equal number of clustering and spreading types ( p ) and no agents can change their type ( r ).
Table 2 . Average aggregate K per type in three diverse constant environments
We see that the game asymmetrically favors spreaders — you do not do nearly as horribly at the different visions . We will consider this when evaluating comparative utilities across groups in future analyses .
Table 3 presents average aggregate outcomes over 30 runs with varying environmental turbulence . Specifically , I vary the probability q that the agents ’ vision will change at any time step . As above , there are initially 50 spreading and 50 clustering agents with probability of changing types ( r .
Table 3 . Average aggregate K per type in changing environments
For the final base case , we consider how each type performs in a homogeneous society : how well do clustering agents perform in the absence of spreading , and vice versa ? Table 4 presents the average K per type over 30 runs when only one type is present . Both q and r = 0 .
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