1. A method for automatically maintaining an autonomic computing system in a steady state, the autonomic computing system having a plurality of parameters, each parameter having one or more thresholds, the autonomic computing system having a plurality of influencers, adjustment of the influencers affecting values of the parameters, the method comprising: in response to determining that one or more of the parameters are each reaching one of the thresholds of the parameter, the one or more of the parameters referred to as to-be-affected parameters, identifying each to-be-affected parameter and the thresholds of the to-be-affected parameter; for each influencer, determining a correlation value between the influencer and each to-be-affected parameter; and, adjusting one or more of the influencers so that the to-be-affected parameters return to more-normal values, based on the correlation values determined, wherein the influencers that are each distinctly associated with the parameters are referred to as distinct influencers, such that adjustment of each distinct influencer affects the value of only one of the parameters, wherein the influencers that are each commonly associated with more than one of the parameters are referred to as common influencers, such that adjustment of each common influencer affects the values of more than one of the parameters, and wherein adjusting one or more of the influencers so that the to-be-affected parameters return to more-normal values comprises: where the to-be-affected parameters are equal to one in number and referred to as a single to-be-affected parameter, for each pair of one or more distinct influencer/single to-be-affected parameter pairs in which the correlation value between the distinct influencer and the single to-be-affected parameter is high, adjusting the distinct influencer of the pair so that the single to-be-affected parameter returns to a more-normal value; where the to-be-affected parameters are equal to more than one in number and fluctuate similarly, selecting a first particular common influencer such that the correlation value between the first particular common influencer and each to-be-affected parameter is high; adjusting the first particular common influencer so that the to-be-affected parameters return to more-normal values; where the to-be-affected parameters are equal to more than one in number and fluctuate dissimilarly, selecting a second particular common influencer such that the correlation value between the second particular common influencer and each to-be-affected parameter is absolutely high, and such that the correlation value between the second particular common influencer and each to-be-affected parameter has a sign corresponding to whether the to-be-affected parameter is increasing or decreasing; adjusting the second particular common influencer so that the to-be-affected parameters return to more-normal values.