Patent ID: 11886988
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 9:
10. A method comprising:
performing reinforcement learning in an iterative process that includes:
inputting a current time frame of an action and observation sequence sequentially into a neural network including a plurality of parameters, the action and observation sequence including a plurality of time frames, each time frame including action values and observation values;
approximating a value function of the reinforcement learning using the neural network based on the current time frame to acquire a current reward value;
updating an action selection policy through exploration based on an ε-greedy strategy using the current reward value, including calculating an exploration term ε based on the current reward value and a temperature parameter and updating the temperature parameter using a present value of the temperature parameter and a product of the exploration term and the current reward value; and
training the neural network by updating the plurality of parameters to update the value function.