One-shot imitation method and learning method in a non-stationary environment through multimodal-skill, and apparatus and recording medium thereof

A one-shot imitation method based on an artificial neural network model that adaptively one-shot imitates a video demonstration of an expert, the method comprising:

• a first stage of inferring a semantic skill sequence from a given expert demonstration;
• a second stage of operating an agent to generate state-action pairs in time series and inferring the dynamics of a current state based thereon;
• and
• a third stage of performing an action appropriate for a new domain by combining the inferred semantic skill sequence and inferred dynamics based on currently acquired environmental data and recombining the inferred semantic skill sequence.

A computing device, comprising:

• a memory that stores an artificial neural network model that adaptively one-shot imitates a video demonstration of an expert;
• and
• a processor that executes the artificial neural network model,
• wherein in a learning phase, the artificial neural network model:
• learns to infer a semantic skill sequence from a given expert demonstration;
• learns to infer dynamics based on state-action pairs, which are the minimum units that form an action trajectory of the expert in the given expert demonstration;
• and learns to create an action sequence by combining the inferred semantic skill sequence and dynamics based on given environmental data.