A wire electric discharge machine configured to move an axis in accordance with an axis feed command by a program or an operation of an operator, comprising: a machine learning device configured to perform machine learning of an adjustment target parameter of the axis feed command in the movement of the axis and an adjustment amount of the adjustment target parameter, wherein the machine learning device includes: a state observation section configured to acquire state data as information indicative of a movement state of the axis in the movement of the axis; a reward condition setting section configured to set a reward condition; a reward calculation section configured to calculate a reward based on the state data and the reward condition; an axis feed command adjustment learning section configured to perform the machine learning of an axis feed command adjustment; and an axis feed command output section configured to determine the adjustment target parameter of the axis feed command and the adjustment amount of the adjustment target parameter as an adjustment action based on a result of the machine learning of the axis feed command adjustment by the axis feed command adjustment learning section and the state data, adjust the axis feed command based on the determined adjustment action, and output the adjusted axis feed command, wherein the axis feed command adjustment learning section is configured to perform the machine learning of the axis feed command adjustment based on the adjustment action, the state data acquired by the state observation section after the movement of the axis based on the outputted adjusted axis feed command, and the reward calculated by the reward calculation section, and wherein the adjustment target parameter of the axis feed command includes an abnormal load level of the axis. a machine learning device configured to perform machine learning of an adjustment target parameter of the axis feed command in the movement of the axis and an adjustment amount of the adjustment target parameter, wherein the machine learning device includes: a state observation section configured to acquire state data as information indicative of a movement state of the axis in the movement of the axis; a reward condition setting section configured to set a reward condition; a reward calculation section configured to calculate a reward based on the state data and the reward condition; an axis feed command adjustment learning section configured to perform the machine learning of an axis feed command adjustment; and an axis feed command output section configured to determine the adjustment target parameter of the axis feed command and the adjustment amount of the adjustment target parameter as an adjustment action based on a result of the machine learning of the axis feed command adjustment by the axis feed command adjustment learning section and the state data, adjust the axis feed command based on the determined adjustment action, and output the adjusted axis feed command, wherein the axis feed command adjustment learning section is configured to perform the machine learning of the axis feed command adjustment based on the adjustment action, the state data acquired by the state observation section after the movement of the axis based on the outputted adjusted axis feed command, and the reward calculated by the reward calculation section, and wherein the adjustment target parameter of the axis feed command includes an abnormal load level of the axis. a state observation section configured to acquire state data as information indicative of a movement state of the axis in the movement of the axis; a reward condition setting section configured to set a reward condition; a reward calculation section configured to calculate a reward based on the state data and the reward condition; an axis feed command adjustment learning section configured to perform the machine learning of an axis feed command adjustment; and an axis feed command output section configured to determine the adjustment target parameter of the axis feed command and the adjustment amount of the adjustment target parameter as an adjustment action based on a result of the machine learning of the axis feed command adjustment by the axis feed command adjustment learning section and the state data, adjust the axis feed command based on the determined adjustment action, and output the adjusted axis feed command, wherein the axis feed command adjustment learning section is configured to perform the machine learning of the axis feed command adjustment based on the adjustment action, the state data acquired by the state observation section after the movement of the axis based on the outputted adjusted axis feed command, and the reward calculated by the reward calculation section, and wherein the adjustment target parameter of the axis feed command includes an abnormal load level of the axis.