Search Results for author: Annie Xie

Found 10 papers, 2 papers with code

Robust Policy Learning over Multiple Uncertainty Sets

no code implementations14 Feb 2022 Annie Xie, Shagun Sodhani, Chelsea Finn, Joelle Pineau, Amy Zhang

Reinforcement learning (RL) agents need to be robust to variations in safety-critical environments.

Influencing Towards Stable Multi-Agent Interactions

no code implementations5 Oct 2021 Woodrow Z. Wang, Andy Shih, Annie Xie, Dorsa Sadigh

Instead of reactively adapting to the other agent's (opponent or partner) behavior, we propose an algorithm to proactively influence the other agent's strategy to stabilize -- which can restrain the non-stationarity caused by the other agent.

Autonomous Driving

Lifelong Robotic Reinforcement Learning by Retaining Experiences

no code implementations19 Sep 2021 Annie Xie, Chelsea Finn

Multi-task learning ideally allows robots to acquire a diverse repertoire of useful skills.

Multi-Task Learning reinforcement-learning

Learning Latent Representations to Influence Multi-Agent Interaction

no code implementations12 Nov 2020 Annie Xie, Dylan P. Losey, Ryan Tolsma, Chelsea Finn, Dorsa Sadigh

We propose a reinforcement learning-based framework for learning latent representations of an agent's policy, where the ego agent identifies the relationship between its behavior and the other agent's future strategy.

reinforcement-learning

Deep Reinforcement Learning amidst Lifelong Non-Stationarity

no code implementations ICML Workshop LifelongML 2020 Annie Xie, James Harrison, Chelsea Finn

As humans, our goals and our environment are persistently changing throughout our lifetime based on our experiences, actions, and internal and external drives.

online learning reinforcement-learning

Learning Predictive Models From Observation and Interaction

no code implementations ECCV 2020 Karl Schmeckpeper, Annie Xie, Oleh Rybkin, Stephen Tian, Kostas Daniilidis, Sergey Levine, Chelsea Finn

Learning predictive models from interaction with the world allows an agent, such as a robot, to learn about how the world works, and then use this learned model to plan coordinated sequences of actions to bring about desired outcomes.

Improvisation through Physical Understanding: Using Novel Objects as Tools with Visual Foresight

no code implementations11 Apr 2019 Annie Xie, Frederik Ebert, Sergey Levine, Chelsea Finn

Machine learning techniques have enabled robots to learn narrow, yet complex tasks and also perform broad, yet simple skills with a wide variety of objects.

Imitation Learning Self-Supervised Learning

Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control

1 code implementation3 Dec 2018 Frederik Ebert, Chelsea Finn, Sudeep Dasari, Annie Xie, Alex Lee, Sergey Levine

Deep reinforcement learning (RL) algorithms can learn complex robotic skills from raw sensory inputs, but have yet to achieve the kind of broad generalization and applicability demonstrated by deep learning methods in supervised domains.

reinforcement-learning

Few-Shot Goal Inference for Visuomotor Learning and Planning

no code implementations30 Sep 2018 Annie Xie, Avi Singh, Sergey Levine, Chelsea Finn

To that end, we formulate the few-shot objective learning problem, where the goal is to learn a task objective from only a few example images of successful end states for that task.

reinforcement-learning Visual Navigation

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