Abstract: A method may include sending a query to one of a cobot or an LLM, where the query may be formed to trigger the cobot to perform a target objective, and where the LLM may be constrained to respond to requests to cause the cobot to perform a given objective with a set of human-readable discrete tasks to accomplish the given objective. The method may also include receiving a target set of human-readable discrete tasks from the LLM, where the target set of human-readable discrete tasks may correspond to target computer-readable code that is configured to cause the cobot to perform the target objective. The method may additionally include auditing the target set of human-readable discrete tasks, and, based on the target set of human-readable discrete tasks passing the audit, authorizing the cobot to implement the target computer-readable code to perform the target objective.

Abstract: Systems and methods for automated response to natural language instructions in accordance with embodiments of the invention are illustrated. One embodiment includes a method for training an agent, the method including sampling an instruction and observation pair from a dataset, predicting a skill code, using a skill predictor, based on the instruction and observation pair, predicting, for each of a plurality of timesteps, a set of one or more actions based on the predicted skill code and a state history using a policy, and updating the skill predictor and the policy based on a comparison of the predicted set of actions and the observation. In many embodiments, the trained agent can then be used to carry out natural language instructions.

Abstract: Systems and methods for imitation learning in accordance with embodiments of the invention are illustrated. One embodiment includes a method for imitation learning. The method includes steps for initializing a Q-function, training the Q-function using a non-adversarial objective based on a set of one or more expert trajectories, and determining a policy based on the trained Q-function.