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OpenAI Baselines: ACKTR & A2C

OpenAI Baselines: ACKTR & A2C

8 years ago 6 Add to circle
More on Dota 2

More on Dota 2

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Dota 2

Dota 2

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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

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Hindsight Experience Replay

Hindsight Experience Replay

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Teacher–student curriculum learning

Teacher–student curriculum learning

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Faster physics in Python

Faster physics in Python

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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

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OpenAI Baselines: DQN

OpenAI Baselines: DQN

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Robots that learn

Robots that learn

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Roboschool

Roboschool

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Equivalence between policy gradients and soft Q-learning

Equivalence between policy gradients and soft Q-le...

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Stochastic Neural Networks for hierarchical reinforcement learning

Stochastic Neural Networks for hierarchical reinfo...

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Unsupervised sentiment neuron

Unsupervised sentiment neuron

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Spam detection in the physical world

Spam detection in the physical world

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Evolution strategies as a scalable alternative to reinforcement learning

Evolution strategies as a scalable alternative to ...

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One-shot imitation learning

One-shot imitation learning

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Distill

Distill

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Learning to communicate

Learning to communicate

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Emergence of grounded compositional language in multi-agent populations

Emergence of grounded compositional language in mu...

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Prediction and control with temporal segment models

Prediction and control with temporal segment model...

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Third-person imitation learning

Third-person imitation learning

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Attacking machine learning with adversarial examples

Attacking machine learning with adversarial exampl...

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Adversarial attacks on neural network policies

Adversarial attacks on neural network policies

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Team update

Team update

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PixelCNN++: Improving the PixelCNN with discretized logistic mixture likelihood and other modifications

PixelCNN++: Improving the PixelCNN with discretize...

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Faulty reward functions in the wild

Faulty reward functions in the wild

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Universe

Universe

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OpenAI and Microsoft

OpenAI and Microsoft

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#Exploration: A study of count-based exploration for deep reinforcement learning

#Exploration: A study of count-based exploration f...

9 years ago 4 Add to circle
On the quantitative analysis of decoder-based generative models

On the quantitative analysis of decoder-based gene...

9 years ago 7 Add to circle
A connection between generative adversarial networks, inverse reinforcement learning, and energy-based models

A connection between generative adversarial networ...

9 years ago 5 Add to circle
RL²: Fast reinforcement learning via slow reinforcement learning

RL²: Fast reinforcement learning via slow reinforc...

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Variational lossy autoencoder

Variational lossy autoencoder

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Extensions and limitations of the neural GPU

Extensions and limitations of the neural GPU

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Semi-supervised knowledge transfer for deep learning from private training data

Semi-supervised knowledge transfer for deep learni...

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Report from the self-organizing conference

Report from the self-organizing conference

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Transfer from simulation to real world through learning deep inverse dynamics model

Transfer from simulation to real world through lea...

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Infrastructure for deep learning

Infrastructure for deep learning

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Machine Learning Unconference

Machine Learning Unconference

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Special projects

Special projects

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Concrete AI safety problems

Concrete AI safety problems

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OpenAI technical goals

OpenAI technical goals

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Generative models

Generative models

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Adversarial training methods for semi-supervised text classification

Adversarial training methods for semi-supervised t...

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