Controlling a robot during interaction with a human

A system comprising:

• one or more processors to cause a first agent to move relative to at least one first target to be held by at least one moving first holder while avoiding colliding with the at least one moving first holder using one or more neural networks, the one or more neural networks to be trained, at least in part, by:
• obtaining network parameters by using at least one demonstration to guide training the one or more neural networks to cause a second agent to move relative to at least one second target held by at least one non-moving second holder while avoiding colliding with the at least one non-moving second holder, and
• modifying the network parameters by training the one or more neural networks to cause the second agent to move relative to at least one third target held by at least one moving third holder while avoiding colliding with the at least one moving third holder;
• and
• one or more memories to store the one or more neural networks.

A processor comprising:

• one or more arithmetic logic units (ALUs) to maneuver a first agent to avoid collision with a first participant comprising a real-world living participant or at least a portion of a virtual character using one or more neural networks trained, at least in part, by:
• performing a first portion of training one or more neural networks, the first portion of the training comprising using at least one first expert demonstration of maneuvering a second agent with respect to a first target held by a stationary second participant to guide training the one or more neural networks;
• and
• performing a second portion of the training the one or more neural networks, the second portion of the training comprising using one or more actions output by the one or more neural networks operating with parameter values determined during the first portion of the training and at least one second expert demonstration of maneuvering a third agent with respect to a second target held by a non-stationary third participant to train the one or more neural networks.