情境
Illustrates the iterative process of a deep Q-network (DQN) agent training in a game environment, from initialization to model saving.
這張圖裡有什麼
看懂背後的決策。
01
Is the replay buffer large enough to sample?
02
Should the target network be updated?
03
Has the episode terminated?
04
Have max episodes been reached?
When designing or explaining reinforcement learning training pipelines, particularly for game AI or simulation-based agents using experience replay.