A method of operating a system comprising a first electronic device and a second electronic device, the method comprising: generating, by the first electronic device, a decision-making data structure using a machine learning data structure, wherein the machine learning data structure comprise data regarding a plurality of states, and data regarding a plurality of possible actions for each of the plurality of states; transmitting, from the first electronic device, to a second electronic device, the decision-making data structure; receiving, by the first electronic device, from the second electronic device, result data regarding a result of performing a selected action selected using the decision-making data structure; and updating, by the first electronic device, the machine learning data structure using the result data, wherein the decision-making data structure includes a look-up table that consists of: data regarding the plurality of states, data regarding one action only to be selected for each of the plurality of states, and additional information indicating whether the data regarding each of the plurality of states is complete or whether more data is needed, wherein the additional information is used by the second electronic device to decide whether or not a randomly-selected action is to be taken instead of the action specified in the decision-making data structure for a current state, wherein the plurality of states comprise CPU/GPU load, frames per second and temperature of the second electronic device, and the one action in the decision-making data structure comprises setting a processor frequency of the second electronic device. generating, by the first electronic device, a decision-making data structure using a machine learning data structure, wherein the machine learning data structure comprise data regarding a plurality of states, and data regarding a plurality of possible actions for each of the plurality of states; transmitting, from the first electronic device, to a second electronic device, the decision-making data structure; receiving, by the first electronic device, from the second electronic device, result data regarding a result of performing a selected action selected using the decision-making data structure; and updating, by the first electronic device, the machine learning data structure using the result data, wherein the decision-making data structure includes a look-up table that consists of: data regarding the plurality of states, data regarding one action only to be selected for each of the plurality of states, and additional information indicating whether the data regarding each of the plurality of states is complete or whether more data is needed, wherein the additional information is used by the second electronic device to decide whether or not a randomly-selected action is to be taken instead of the action specified in the decision-making data structure for a current state, wherein the plurality of states comprise CPU/GPU load, frames per second and temperature of the second electronic device, and the one action in the decision-making data structure comprises setting a processor frequency of the second electronic device. data regarding the plurality of states, data regarding one action only to be selected for each of the plurality of states, and additional information indicating whether the data regarding each of the plurality of states is complete or whether more data is needed, wherein the additional information is used by the second electronic device to decide whether or not a randomly-selected action is to be taken instead of the action specified in the decision-making data structure for a current state, wherein the plurality of states comprise CPU/GPU load, frames per second and temperature of the second electronic device, and the one action in the decision-making data structure comprises setting a processor frequency of the second electronic device.