A machine learning device, which performs a task using a plurality of industrial machines and learns task sharing for the plurality of industrial machines, includes a state variable observation unit which observes state variables of the plurality of industrial machines; and a learning unit which learns task sharing for the plurality of industrial machines, on the basis of the state variables observed by the state variable observation unit.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A machine learning device which performs a task using a plurality of industrial machines and learns task sharing for the plurality of industrial machines, the device comprising: a state variable observation unit which observes state variables of the plurality of industrial machines; and a learning unit which learns task sharing for the plurality of industrial machines, on the basis of the state variables observed by the state variable observation unit. 2. The machine learning device according to claim 1, further comprising a decision unit which decides and issues, as a command, a sharing detail of the task for the plurality of industrial machines by referring to the task sharing learned by the learning unit. 3. The machine learning device according to claim 2, wherein the machine learning device is connected to each of the plurality of industrial machines via a network, the state variable observation unit obtains the state variables of the plurality of industrial machines via the network, and the decision unit sends the sharing detail of the task to the plurality of industrial machines via the network. 4. The machine learning device according to claim 1, wherein the state variable observation unit observes at least one of a task time from start to end of a series of tasks repeatedly performed by the plurality of industrial machines, and a task load on each of the plurality of industrial machines in an interval from the start to the end of the tasks, or observes at least one of an achievement level of the tasks performed by the plurality of industrial machines and a difference in task volume in each of the plurality of industrial machines. 5. The machine learning device according to claim 4, wherein the state variable observation unit further obtains at least one of a change in production volume in an upstream process, and a change in production volume upon stop of the industrial machine for maintenance performed periodically. 6. The machine learning device according to claim 1, wherein the learning unit learns task sharing for maintaining a volume of production by the plurality of industrial machines, averaging a load on each of the plurality of industrial machines, and maximizing a volume of the task performed by the plurality of industrial machines. 7. The machine learning device according to claim 1, wherein each of the plurality of industrial machines comprises a robot, and the plurality of robots perform the task on the basis of the learned task sharing. 8. The machine learning device according to claim 1, wherein the learning unit comprises: a reward computation unit which computes a reward on the basis of output from the state variable observation unit; and a value function update unit which updates a value function for determining a value of task sharing for the plurality of industrial machines, in accordance with the reward on the basis of output from the state variable observation unit and output from the reward computation unit. 9. The machine learning device according to claim 1, wherein the learning unit comprises: an error computation unit which computes an error on the basis of input teacher data and output from the state variable observation unit; and a learning model update unit which updates a learning model for determining an error of task sharing for the plurality of industrial machines, on the basis of output from the state variable observation unit and output from the error computation unit. 10. The machine learning device according to claim 1, wherein the machine learning device further comprises a neural network. 11. An industrial machine cell comprising the plurality of industrial machines; and the machine learning device according to claim 1. 12. A manufacturing system comprising a plurality of industrial machine cells according to claim 11, wherein the machine learning devices are provided in correspondence with the industrial machine cells, and the machine learning devices provided in correspondence with the industrial machine cells are configured to share or exchange data with each other via a communication medium. 13. The manufacturing system according to claim 12, wherein the machine learning device is located on a cloud server. 14. A machine learning method for performing a task using a plurality of industrial machines and learning task sharing for the plurality of industrial machines, the method comprising: observing state variables of the plurality of industrial machines; and learning task sharing for the plurality of industrial machines, on the basis of the observed state variables. 15. The machine learning method according to claim 14, wherein observing the state variables comprises one of: observing at least one of a task time from start to end of a series of tasks repeatedly performed by the plurality of industrial machines, and a task load on each of the plurality of industrial machines in an interval from the start to the end of the tasks, and observing at least one of an achievement level of the tasks performed by the plurality of industrial machines and a difference in task volume in each of the plurality of industrial machines.