<p>If you replaced the Q-table of an untrained SAC model with a trained DDPG's Q-table then you'd be using a converged policy produced from the DDPG method. Likewise, replacing an untrained DDPG model's Q-table with the Q-table from a trained SAC model will give it the converged policy from following the SAC method.</p>

<p>If you have not already, you should check out <a href="https://arxiv.org/pdf/1801.01290.pdf" rel="nofollow noreferrer">this paper</a> which discusses and experiments with the differences between DDPG and SAC.</p>
Using training data for training another model
<p>I'm working on NIPS 2017 Learning to Run project. I have limited time and I need to try 2 models(DDPG and Soft Actor Critic). The simulation is slow and it takes too much time.
I wonder, 
After I trained one of them, is it possible to use its state-action-reward data for training the other one?</p>