System and method for computer-assisted design of inductor for voltaged-controlled oscillator

A computing system comprising:

• a memory storing instructions;
• and
• one or more processing units coupled to the memory;
• wherein the processing unit is configured for execution of the instructions to cause the computing system to:
• receive target specifications for an inductor;
• generate an inductor design segment-by-segment using a reinforcement learning agent to generate segment parameters for each added segment, wherein the reinforcement learning agent implements a policy that is learned using a reward computed based on performance of the generated inductor design relative to the target specifications, wherein the inductor design is generated segment-by-segment by:
• inputting to the reinforcement learning agent a current inductor state representing any existing segments of the inductor design;
• obtaining, using the policy implemented by the reinforcement learning agent and based on the inputted current inductor state, segment parameters for a new segment to be added to the inductor design;
• updating the current inductor state to connect the new segment to any existing segments in the inductor design, in accordance with the segment parameters obtained from the reinforcement learning agent;
• and
• repeating the inputting, obtaining and updating until a termination condition is met;
• and
• output the generated inductor design as the candidate inductor design after determining that the generated inductor design satisfies a predefined performance threshold.

A non-transitory computer readable medium having instructions encoded thereon, wherein the instructions, when executed by a processing unit of a computing system, cause the computing system to:

• receive target specifications for an inductor;
• generate an inductor design segment-by-segment using a reinforcement learning agent to generate segment parameters for each added segment, wherein the reinforcement learning agent implements a policy that is learned using a reward computed based on performance of the generated inductor design relative to the target specifications, wherein the inductor design is generated segment-by-segment by:
• inputting to the reinforcement learning agent a current inductor state representing any existing segments of the inductor design;
• obtaining, using the policy implemented by the reinforcement learning agent and based on the inputted current inductor state, segment parameters for a new segment to be added to the inductor design;
• updating the current inductor state to connect the new segment to any existing segments in the inductor design, in accordance with the segment parameters obtained from the reinforcement learning agent;
• and
• repeating the inputting, obtaining and updating until a termination condition is met;
• and
• output the generated inductor design as the candidate inductor design after determining that the generated inductor design satisfies a predefined performance threshold.