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Friday, January 25 • 10:45am - 11:05am
Control Algorithms for Imitation Learning from Observation

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Imitation learning is a paradigm that enables autonomous agents to capture behaviors that are demonstrated by people or other agents. Effective approaches, such as Behavioral Cloning and Inverse Reinforcement Learning, tend to rely on the learning agent being aware of the low-level actions being demonstrated.  However, in many cases, such as videos or demonstrations from people (or any agent with a different morphology), the learning agent only has access to observed state transitions.  This talk introduces two novel control algorithms for imitation learning from observation: Behavioral Cloning from Observation (BCO) and Generative Adversarial Imitation from Observation (GAIfO).


Speakers
avatar for Peter Stone, University of Texas

Peter Stone, University of Texas

Founder & Director of the Learning Agents Research Group, University of Texas
I am the founder and director of the Learning Agents Research Group (LARG) within the Artificial Intelligence Laboratory in the Department of Computer Science at The University of Texas at Austin, as well as associate department chair and chair of the University's Robotics Portfolio... Read More →


Friday January 25, 2019 10:45am - 11:05am
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA