Abstract: A method of reinforcement learning of a neural network device for generating a verification vector for verifying a circuit design comprising a circuit block includes inputting a test vector to the circuit block, generating one or more rewards based on a coverage corresponding to the test vector, the coverage being determined based on a state transition of the circuit block based on the test vector, and applying the one or more rewards to a reinforcement learning.

Abstract: The present invention relates generally to the field of molecular biology and concerns a method for enhancing yield-related traits in plants by modulating expression in a plant of a nucleic acid encoding an SGT1 polypeptide, or a CLC-pKG polypeptide, or a HD-hydrolase-like polypeptide. The present invention also concerns plants having modulated expression of a nucleic acid encoding an SGT1 polypeptide, or a CLC-pKG polypeptide, or a HD-hydrolase-like polypeptide, which plants have enhanced yield-related traits relative to corresponding wild type plants or other control plants. The invention also provides constructs useful in the methods of the invention.