Patent ID: 11907335
Assignee: COGNITIVE SPACE
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 15:
16. The method of claim 11, further comprises:
generating an actual reward value corresponding to the desired target upon executing the generated one or more actions by the agent by using the trained policy network based ANN model;
computing an error in the expected reward value corresponding to the desired target based on difference between the expected reward value and the actual reward value by using the trained value network based ANN model;
updating learning of the trained value network based ANN model based on the computed error by using reinforcement learning, wherein reinforcement learning is performed by using Stochastic Gradient Descent (SGD), wherein the trained value network based ANN model updates one or more value network parameters based on the computed error and wherein the learning of the trained value network based ANN model is updated for one or more training sessions until a desired expected reward value is achieved based on the computed error;
generating an updated expected reward value for each of the one or more targets by applying the received request and the one or more input parameters to the updated trained value network based ANN model; and
determining a different target among the one or more targets based on the updated expected reward value of each of the one or more targets by using the updated trained value network based ANN model, wherein the updated expected reward value associated with the different target corresponds to a higher updated expected reward value.