Task planning using machine learning models

A system comprising:

• one or more computers;
• and
• one or more storage devices storing instructions that when executed by the one or more computers, cause the one or more computers to perform the operations comprising:
• receiving a query comprising a request to generate a plan for an input task;
• obtaining candidate example data defining a plurality of candidate task-plan examples, wherein each candidate task-plan example comprises (i) a respective example task and (ii) a respective example plan for achieving the respective example task;
• obtaining data defining an initial plan for the input task, wherein the initial plan comprises an initial action sequence that includes a sequence of a plurality of actions;
• computing, for each of the plurality of candidate task-plan examples, a respective action sequence similarity score measuring a similarity between (i) the initial action sequence and (ii) a respective action sequence included in the respective example plan in the candidate task-plan examples;
• selecting, using the action sequence similarity scores, a set of task-plan examples from the plurality of candidate task-plan examples;
• and
• processing, using a generative machine learning model, (i) the query and (ii) one or more prompt inputs generated using the selected set of task-plan examples, to generate an output plan.

One or more computer-readable storage media storing instructions that, when executed by one or more computers, cause the one or more computers to perform the operations of comprising:

• receiving a query comprising a request to generate a plan for an input task;
• obtaining candidate example data defining a plurality of candidate task-plan examples, wherein each candidate task-plan example comprises (i) a respective example task and (ii) a respective example plan for achieving the respective example task;
• obtaining data defining an initial plan for the input task, wherein the initial plan comprises an initial action sequence that includes a sequence of a plurality of actions;
• computing, for each of the plurality of candidate task-plan examples, a respective action sequence similarity score measuring a similarity between (i) the initial action sequence and (ii) a respective action sequence included in the respective example plan in the candidate task-plan examples;
• selecting, using the action sequence similarity scores, a set of task-plan examples from the plurality of candidate task-plan examples;
• and
• processing, using a generative machine learning model, (i) the query and (ii) one or more prompt inputs generated using the selected set of task-plan examples, to generate an output plan.