Data-efficient demonstration expansion for training a generalist robotic agent

A system comprising:

• at least one data processor;
• a non-volatile machine-readable memory comprising instructions that, when applied to the at least one data processor, configure the system to, for each task represented in a plurality of task configurations for a robot:
• (a) compute a probability for sampling an initial state setting for the task;
• (b) based on the probability, sample the initial state setting from a plurality of initial state settings for the task;
• (c) evaluate an outcome of the task from the initial state setting over a trajectory;
• (d) on condition that the outcome fails, acquire new trajectories for the task that begin at the initial state setting, and add the new trajectories to a training set for the task;
• (e) merge the training set for the task into a total training set for the robot;
• and
• repeat (a) through (e) until the robot's performance on a policy comprising the plurality of task configurations satisfies a condition, or a computing resource budget is met.

A non-volatile machine-readable memory comprising instructions that, when applied to at least one data processor, configure the at least one data processor to, for each task represented in a plurality of task configurations for a robot:

• (a) compute a probability for sampling an initial state setting for the task;
• (b) based on the probability, sample the initial state setting from a plurality of initial state settings for the task;
• (c) evaluate an outcome of the task from the initial state setting over a trajectory;
• (d) on condition that the outcome fails, acquire new trajectories for the task that begin at the initial state setting, and add the new trajectories to a training set for the task;
• (e) merge the training set for the task into a total training set for the robot;
• and
• repeat (a) through (e) until the robot's performance on a policy comprising the plurality of task configurations satisfies a condition, or a computing resource budget is met.