Systems and methods for machine learning using a network of decision-making nodes

An apparatus for machine learning, comprising:

• at least one processor;
• and
• at least one memory in electronic communication with the processor, the at least one memory storing instructions that are executable by the at least one processor to:
• obtain a set of inputs;
• search the at least one memory for a node uniquely associated with the set of inputs;
• if a node uniquely associated with the set of inputs is not found in the at least one memory:
• create the node in the at least one memory;
• associate the node with the set of inputs in the at least one memory;
• randomly generate a decision set using a random number generator;
• receive a score evaluating the decision set at solving a problem;
• and
• store, in the at least one memory in association with the node, the decision set with the score for the decision set;
• and
• if the node uniquely associated with the set of inputs is found in the at least one memory:
• retrieve, from the at least one memory, a decision set associated with the node with a best previous score;
• responsive to a value of a randomness factor, either output, via an output device, the decision set with the best previous score as a best solution to the problem or generate a new decision set, wherein the new decision set is either the same as the retrieved decision set or is randomized, wherein a chance of the new decision set being randomized is determined by the randomness factor;
• and
• if a new decision set is generated:
• receive a score evaluating the new decision set at solving the problem;
• and
• store, in the at least one memory in association with the node, the new decision set and the score for the new decision set;
• wherein each node is a decision-making neuron in network of decision-making neurons.