A method for determining a variable near-optimal policy for a problem formulated as Markov Decision Process, the problem comprising at least one limited action entry, the limited action entry being an entry of an action of a finite set of actions limited in the number of times its value may be changed, the method comprising using at least one hardware processor for: receiving data elements with respect to the problem, the data elements comprising: (a) a finite set of states, (b) the finite set of actions, (c) a transition probabilities matrix determining transition probabilities between states of the finite set of states, once actions of the set of actions are performed; (d) an immediate cost function, wherein the value of the immediate cost function is determined for a pair of a state of the finite set of states and an action of the finite set of actions, and (e) a discount factor; updating one or more data elements of the received data elements relating to the at least one limited action entry, wherein the one or more data elements are selected from the group consisting of: the transition probabilities matrix, the immediate cost function and the discount factor, and wherein the updating is triggered by a change of a value of a limited action entry of the at least one limited action entry; and following the updating of the one or more data elements, calculating a current near-optimal policy for the problem based on the updated one or more data elements.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for determining a variable near-optimal policy for a problem formulated as Markov Decision Process, the problem comprising at least one limited action entry, the limited action entry being an entry of an action of a finite set of actions limited in the number of times its value may be changed, the method comprising using at least one hardware processor for: receiving data elements with respect to the problem, the data elements comprising: (a) a finite set of states, wherein each state of the states comprises state entries, (b) the finite set of actions, wherein each action of the actions comprises action entries, (c) a transition probabilities matrix determining transition probabilities between states of the finite set of states, once actions of the set of actions are performed; (d) an immediate cost function, wherein the value of the immediate cost function is determined for a pair of a state of the finite set of states and an action of the finite set of actions, and (e) a discount factor; updating one or more data elements of the received data elements relating to the at least one limited action entry, wherein the one or more data elements are selected from the group consisting of: the transition probabilities matrix, the immediate cost function and the discount factor, and wherein the updating is triggered by a change in a value of a limited action entry of the at least one limited action entry; and following the updating of the one or more data elements, calculating a current near-optimal policy for the problem based on the updated one or more data elements. 2. The method of claim 1, wherein the updating of the one or more data elements comprises updating the immediate cost function. 3. The method of claim 2, wherein the updating of the immediate cost function comprises increasing a value of the immediate cost function determined for the limited action entry, for the next time the value of the limited action entry is changed. 4. The method of claim 1, wherein the updating of the one or more data elements comprises updating the discount factor. 5. The method of claim 4, wherein the updating of the discount factor comprises increasing the discount factor with respect to the number of times remained to change the value of the limited action entry. 6. The method of claim 1, wherein the updating of the one or more data elements comprises updating the transition probabilities matrix. 7. The method of claim 1, wherein the updating of the one or more data elements comprises calculating a current value for the one or more data elements. 8. The method of claim 1, further comprising using said at least one hardware processor for preventing the updating of the one or more data elements for a number of times which is beyond the number of times the value of the limited action entry may be changed. 9. The method of claim 1, wherein the discount factor is used to control a bounded gap of the calculated current near-optimal policy to optimality. 10. A computer program product for determining a variable near-optimal policy for a problem formulated as Markov Decision Process, the problem comprising at least one limited action entry, the limited action entry being an entry of an action of a finite set of actions limited in the number of times its value may be changed, the computer program product comprising a non-transitory computer-readable storage medium having program code embodied therewith, the program code executable by at least one hardware processor to: receive data elements with respect to the problem, the data elements comprising: (a) a finite set of states, (b) the finite set of actions, (c) a transition probabilities matrix determining transition probabilities between states of the finite set of states, once actions of the set of actions are performed; (d) an immediate cost function, wherein the value of the immediate cost function is determined for a pair of a state of the finite set of states and an action of the finite set of actions, and (e) a discount factor; update one or more data elements of the received data elements relating to the at least one limited action entry, wherein the one or more data elements are selected from the group consisting of: the transition probabilities matrix, the immediate cost function and the discount factor, and wherein the updating is triggered by a change of a value of a limited action entry of the at least one limited action entry; and following the updating of the one or more data elements, calculate a current near-optimal policy for the problem based on the updated one or more data elements. 11. The computer program product of claim 10, wherein the updating of the one or more data elements comprises updating the immediate cost function. 12. The computer program product of claim 11, wherein the updating of the immediate cost function comprises increasing a value of the immediate cost function determined for the limited action entry, for the next time the value of the limited action entry is changed. 13. The computer program product of claim 10, wherein the updating of the one or more data elements comprises updating of the discount factor. 14. The computer program product of claim 12, wherein the updating of the discount factor comprises increasing the discount factor with respect to the number of times remained to change the value of the limited action entry. 15. The computer program product of claim 10, wherein the updating of the one or more data elements comprises updating the transition probabilities matrix. 16. The computer program product of claim 10, wherein the updating of the one or more data elements comprises calculating a current value for the one or more data elements. 17. The computer program product of claim 10, wherein said program code is further executable by said at least one hardware processor to prevent the updating of the one or more data elements for a number of times which is beyond the number of times the value of the limited action entry may be changed. 18. The computer program product of claim 10, wherein the discount factor is used to control a bounded gap of the calculated current near-optimal policy to optimality. 19. A system comprising at least one hardware processor configured to: receive data elements with respect to the problem, the data elements comprising: (a) a finite set of states, (b) the finite set of actions, (c) a transition probabilities matrix determining transition probabilities between states of the finite set of states, once actions of the set of actions are performed; (d) an immediate cost function, wherein the value of the immediate cost function is determined for a pair of a state of the finite set of states and an action of the finite set of actions, and (e) a discount factor; update one or more data elements of the received data elements relating to the at least one limited action entry, wherein the one or more data elements are selected from the group consisting of: the transition probabilities matrix, the immediate cost function and the discount factor, and wherein the updating is triggered by a change of a value of a limited action entry of the at least one limited action entry; and following the updating of the one or more data elements, calculate a current near-optimal policy for the problem based on the updated one or more data elements. 20. The system of claim 19, wherein the updating of the one or more data elements comprises calculating a current value for the one or more data elements.