![]() ![]() Comparing with the fully centralized methods, this design can reduce the communication burden by only sending limited information to the global level during the learning process. These two structures work together to generate the optimal control action for each agent and to achieve better cooperation in the games. ![]() ![]() Then, the global actor-critic structure is built to provide the local design an overall view of the combat based on the limited centralized information, such as the health value. The local actor-critic structure is established for each kind of agents with partially observable information received from the environment. Specifically, we design a two-level actor-critic structure to help the agents with interactions and cooperation in the StarCraft combat. In this article, we propose a novel semicentralized deep deterministic policy gradient (SCDDPG) algorithm for cooperative multiagent games.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |