Training design generative models using simulation

One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of:

• receiving requirement data;
• performing, using a simulator and a first trained machine learning model, one or more operations to generate one or more preferred designs and one or more rejected designs, wherein the first trained machine learning model is trained to generate one or more first designs based on the requirement data;
• performing, based on the requirement data, the one or more preferred designs, and the one or more rejected designs, one or more training operations to retrain the first trained machine learning model to generate a second trained machine learning model;
• and
• generating, based on one or more first requirements and using the second trained machine learning model, one or more first predicted designs.

A system, comprising:

• one or more memories storing instructions;
• and
• one or more processors that are coupled to the one or more memories and, when executing the instructions, are configured to:
• receive requirement data;
• perform, using a simulator and a first trained machine learning model, one or more operations to generate one or more preferred designs and one or more rejected designs, wherein the first trained machine learning model is trained to generate one or more first designs based on the requirement data;
• perform, based on the requirement data, the one or more preferred designs, and the one or more rejected designs, one or more training operations to retrain the first trained machine learning model to generate a second trained machine learning model;
• and
• generate, based on one or more first requirements and using the second trained machine learning model, one or more first predicted designs.