Online task inference for compositional tasks with context adaptation

A method for performing a task, comprising:

• generating a first posterior distribution of a global latent context variable for the task based on a pool of contexts sampled from one or more previous episodes of the task;
• generating a second posterior distribution of a local latent context variable for a current time step in a current episode of the task based on one or more recent contexts sampled at one or more previous time steps of the current episode;
• and
• causing an agent to perform an action related to carrying out the task based on the first posterior distribution, the second posterior distribution, and a current state associated with the current time step.

A non-transitory computer readable medium storing instructions that, when executed by a processor, cause the processor to perform the steps of:

• generating a first posterior distribution of a global latent context variable for the task based on a pool of contexts sampled from one or more previous episodes of the task;
• generating a second posterior distribution of a local latent context variable for a current time step in a current episode of the task based on one or more recent contexts sampled at one or more previous time steps of the current episode;
• and
• causing an agent to perform an action related to carrying out the task based on the first posterior distribution, the second posterior distribution, and a current state associated with the current time step.

A system, comprising:

• a memory that stores instructions, and
• a processor that is coupled to the memory and, when executing the instructions, is configured to:
• generate a first posterior distribution of a global latent context variable for the task based on a pool of contexts sampled from one or more previous episodes of the task;
• generate a second posterior distribution of a local latent context variable for a current time step in a current episode of the task based on one or more recent contexts sampled at one or more previous time steps of the current episode;
• and
• cause an agent to perform an action related to carrying out the task based on the first posterior distribution, the second posterior distribution, and a current state associated with the current time step.