Fig. 1
From: Using deep reinforcement learning to speed up collective cell migration
The reinforcement learning framework: leader cell or follower cell which are seen as the agent, continually interact with environment. The agent selects actions and the environment responds to these actions and presents new situations to the agent. The environment also gives rise to rewards, special numerical values that the agent seeks to maximize over time through its choice of actions