Methods and apparatus to adaptively optimize feed blend and medicinal selection using machine learning to optimize animal milk production and health

An apparatus, comprising:

• a memory;
• and
• a hardware processor operatively coupled to the memory, the hardware processor configured to:
• train a machine learning model to receive inputs associated with health status of a managed livestock, receive a value associated with a bioproduct quality of the managed livestock, and identify, by automatically constructing hierarchical states, temporal abstractions based on the inputs and the value to be used to identify a feed selection configured to increase a likelihood of collectively improving the health status of the managed livestock and the bioproduct quality of the managed livestock;
• receive at least one of a target value of the bioproduct quality or a target value of the health status;
• receive a current value of the bioproduct quality and a current indication of the health status of the managed livestock;
• generate a set of feature vectors based on the current value of the bioproduct quality, the current indication of the health status, and the at least one of the target value of the bioproduct quality or the target value of the health status;
• and
• provide the set of feature vectors to the machine learning model to generate, based on the temporal abstractions identified by the machine learning model, an output including a feed selection configured to, upon consumption by the managed livestock, increase a likelihood of collectively improving the health status of the managed livestock and the bioproduct quality of the managed livestock.

A non-transitory processor-readable medium storing code representing instructions to be executed by a processor, the instructions comprising code to cause the processor to:

• receive at least one of a target value of a health status of a managed livestock or a target value of a bioproduct quality of the managed livestock;
• receive an indication of the health status of the managed livestock;
• receive an indication of the bio product quality of the managed livestock;
• generate a set of input vectors based on the at least one of the target value of the health status or the target value of the bioproduct quality, the indication of the bioproduct quality, and the indication of health status;
• and provide the set of input vectors to a machine learning model trained to generate, based on a set of hyperparameters of the machine learning model, an output indicating a feed selection to be used to feed the managed livestock, the feed selection configured to, upon consumption, increase a likelihood of collectively improving the health status of the managed livestock and the bioproduct quality of the managed livestock, the feed selection configured to be included in a feed blend to be administered to the managed livestock, the set of hyperparameters including at least one of a discount factor associated with a weight of future rewards in the machine learning model, or a threshold value to balance between exploration and exploitation within the machine learning model.