Method, apparatus and product for utilizing stochastic controller to provide user-controlled notification rate of wearable-based events. The method comprises obtaining events issued by a module based on analysis of multiple sensor readings of one or more sensors of a wearable device. The method further comprises determining by a stochastic controller whether to provide an alert to a user based on the events and based on a user preference, wherein the user preference is indicative of a desired notification rate of the user, wherein the stochastic controller comprises a stochastic model of an environment. Based on such determination, alerts are outputted to the user.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer-implemented method comprising: obtaining events issued by a module based on analysis of multiple sensor readings of one or more sensors of a wearable device; determining by a stochastic controller whether to provide an alert to a user based on the events and based on a user preference, wherein the user preference is indicative of a desired notification rate of the user, wherein the stochastic controller comprises a stochastic model of an environment; and outputting alerts to the user based on said determining. 2. The computer-implemented method of claim 1, wherein the stochastic controller defining an objective function, wherein the objective function comprises a user-defined weight that is controllable by the user during operation of the wearable device. 3. The computer-implemented method of claim 1, wherein the stochastic controller is based on a Markov Decision Process (MDP), wherein the MDP comprises: a set of states, a set of actions, an immediate cost function based on a state and an event, a transition probabilities matrix, and an initial states distribution; wherein said computer-implemented method further comprises computing an optimized policy which minimizes an expected aggregated cost that is based on the immediate cost function; wherein said determining comprises applying the optimized policy. 4. The computer-implemented method of claim 3, wherein the transition probabilities matrix is computed based on historical data. 5. The computer-implemented method of claim 4, wherein the transition probabilities matrix is updated based on current data provided by the analytics library, wherein the method further comprises re-computing a new optimized policy which minimizes the expected aggregated cost function in view of the updated probabilities matrix; and applying the new optimized policy to perform said determining. 6. The computer-implemented method of claim 3, further comprising: obtaining user feedback to modify the user preference; re-computing a new optimized policy which minimizes the expected aggregated cost function based on the modified user preference; and applying the new optimized policy to perform said determining. 7. The computer-implemented method of claim 1, wherein the wearable device is worn by the user. 8. The computer-implemented method of claim 1, wherein the wearable device is worn by a person that is being monitored by the user. 9. A computerized apparatus having a processor, the processor being adapted to perform the steps of: obtaining events issued by a module based on analysis of multiple sensor readings of one or more sensors of a wearable device; determining by a stochastic controller whether to provide an alert to a user based on the events and based on a user preference, wherein the user preference is indicative of a desired notification rate of the user, wherein the stochastic controller comprises a stochastic model of an environment; and outputting alerts to the user based on said determining. 10. The computerized apparatus of claim 9, wherein the stochastic controller defining an objective function, wherein the objective function comprises a user-defined weight that is controllable by the user during operation of the wearable device. 11. The computerized apparatus of claim 9, wherein the stochastic controller is based on a Markov Decision Process (MDP), wherein the MDP comprises: a set of states, a set of actions, an immediate cost function based on a state and an event, a transition probabilities matrix, and an initial states distribution; wherein said processor is further adapted to perform: computing an optimized policy which minimizes an expected aggregated cost that is based on the immediate cost function; wherein said determining comprises applying the optimized policy. 12. The computerized apparatus of claim 11, wherein the transition probabilities matrix is computed based on historical data. 13. The computerized apparatus of claim 12, wherein the transition probabilities matrix is updated based on current data provided by the analytics library, wherein said processor is further adapted to perform: re-computing a new optimized policy which minimizes the expected aggregated cost function in view of the updated probabilities matrix; and applying the new optimized policy to perform said determining. 14. The computerized apparatus of claim 11, wherein said processor is further adapted to perform: obtaining user feedback to modify the user preference; re-computing a new optimized policy which minimizes the expected aggregated cost function based on the modified user preference; and applying the new optimized policy to perform said determining. 15. The computerized apparatus of claim 9, wherein the wearable device is worn by the user. 16. The computerized apparatus of claim 9, wherein the wearable device is worn by a person that is being monitored by the user. 17. A computer program product comprising a non-transitory computer readable storage medium retaining program instructions, which program instructions when read by a processor, cause the processor to perform a method comprising: obtaining events issued by a module based on analysis of multiple sensor readings of one or more sensors of a wearable device; determining by a stochastic controller whether to provide an alert to a user based on the events and based on a user preference, wherein the user preference is indicative of a desired notification rate of the user, wherein the stochastic controller comprises a stochastic model of an environment; and outputting alerts to the user based on said determining.