Hey,
Epsilon-greedy is used for discrete action spaces. For continuous action spaces, exploration is controlled by adding noise to the action itself.
For setting the noise options for DDPG just check https://de.mathworks.com/help/reinforcement-learning/ref/rlddpgagentoptions.html . For deeper insight you can check the Noise Model itself on https://de.mathworks.com/help/reinforcement-learning/ref/rlddpgagentoptions.html#mw_2875b71d-bfb0-4be4-b0d3-a44592c3cb30_head or the DDPG Paper https://arxiv.org/pdf/1509.02971.pdf .
