Methods and apparatus to generate acceptability criteria for autonomous systems plans

A method of validating commands of an autonomous system, the method comprising:

• compiling data generated by the autonomous system into an autonomous system task dataset;
• encoding the dataset for input into a rule distillation neural network architecture;
• training the rule distillation neural network architecture;
• modifying the rule distillation neural network architecture by adapting it to a new input data domain, the autonomous system task dataset used to train the modified neural network architecture;
• generating formally verified acceptability criteria;
• and
• evaluating a control command, the evaluation to result in an acceptance or rejection of the command.

A non-transitory computer readable storage medium comprising computer readable instructions that, when executed, cause one or more processors to, at least:

• compile data generated by an autonomous system into an autonomous system task dataset;
• encode the dataset for input into a rule distillation neural network architecture;
• train the rule distillation neural network architecture;
• modify the rule distillation neural network architecture by adapting it to a new input data domain, the autonomous system task dataset used to train the modified neural network architecture;
• generate formally verified acceptability criteria;
• and
• evaluate a control command, the evaluation resulting in an acceptance or rejection of the command.

An apparatus for validating commands of an autonomous system, the apparatus comprising:

• means for compiling data generated by the autonomous system into an autonomous system task dataset;
• means for encoding the dataset for input into a rule distillation neural network architecture;
• means for training the rule distillation neural network architecture;
• means for modifying the rule distillation neural network architecture by adapting it to a new input data domain, the autonomous system task dataset used to train the modified neural network architecture;
• a first means for generating formally verified acceptability criteria;
• and
• means for evaluating a control command, the evaluation resulting in an acceptance or rejection of the command.