Patent ID: 11938403
Assignee: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
Field: Furniture, games (Other fields)
Classification: CPC A  G | IPC A

Claim 12:
13. The game character behavior control method according to claim 12, wherein iteratively determining a difference between a total reward value and an assessment value comprises, in each iteration:
inputting a first or second game state information sample into the actor network model, performing feature extraction on the first or second game state information by using the actor network model, to obtain behavior information corresponding to the first or the second game state information sample;
obtaining a reward value determined by a game environment according to the behavior information for each turn in a round of battle;
determining, a total reward value corresponding to the first or the second game state information sample according to the reward value for each turn in the round of battle;
inputting the first or the second game state information sample into the critic network model, and performing feature extraction on the first or second game state information sample using the critic network model, to obtain an assessment value corresponding to the first or the second game state information sample; and
determining a difference between the total reward value and the assessment value associated with the first or the second game state information sample, and adjusting parameters of the reinforcement learning network model or the general-purpose reinforcement learning network model respectively.