OpenAI updates OpenAI-updates

Gathering human feedback Gathering human feedback

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Better exploration with parameter noise Better exploration with parameter noise

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Proximal Policy Optimization Proximal Policy Optimization

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Robust adversarial inputs Robust adversarial inputs

We’ve created images that reliably fool neural network classifiers when viewed from varied scales and perspectives. This challenges a claim from last week that self-driving cars would be hard to trick maliciously since they capture images from multiple scales, angles, perspectives, and the like. We’ve created images that reliably fool neural network classifiers when viewed from varied scales and perspectives. This challenges a claim from last week that self-driving cars would be hard to trick maliciously since they capture images from multiple scales, angles, perspectives, and the like.

Hindsight Experience Replay Hindsight Experience Replay

Teacher–student curriculum learning Teacher–student curriculum learning

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Faster physics in Python Faster physics in Python

We’re open-sourcing a high-performance Python library for robotic simulation using the MuJoCo engine, developed over our past year of robotics research. We’re open-sourcing a high-performance Python library for robotic simulation using the MuJoCo engine, developed over our past year of robotics research.

Learning from human preferences Learning from human preferences

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Learning to cooperate, compete, and communicate Learning to cooperate, compete, and communicate

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UCB exploration via Q-ensembles UCB exploration via Q-ensembles

OpenAI Baselines: DQN OpenAI Baselines: DQN

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Robots that learn Robots that learn

We’ve created a robotics system, trained entirely in simulation and deployed on a physical robot, which can learn a new task after seeing it done once. We’ve created a robotics system, trained entirely in simulation and deployed on a physical robot, which can learn a new task after seeing it done once.