OpenAI News
Report from the OpenAI hackathon
On March 3rd, we hosted our first hackathon with 100 members of the artificial intelligence community.
Topics: Models
Concept
Models
OpenAI News
OpenAI Scholars
We’re providing 6–10 stipends and mentorship to individuals from underrepresented groups to study deep learning full-time for 3 months and open-source a project.
Topics: Models
OpenAI News
Multi-Goal Reinforcement Learning: Challenging robotics environments and request for research
The purpose of this technical report is two-fold. First of all, it introduces a suite of challenging continuous control tasks (integrated with OpenAI Gym) based on currently existing robotics hardware. The tasks include pushing, sliding and pick & place...
Topics: Models
OpenAI News
Ingredients for robotics research
We’re releasing eight simulated robotics environments and a Baselines implementation of Hindsight Experience Replay, all developed for our research over the past year. We’ve used these environments to train models which work on physical robots. We’re also...
Topics: Models
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OpenAI News
OpenAI hackathon
Come to OpenAI’s office in San Francisco’s Mission District for talks and a hackathon on Saturday, March 3rd.
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OpenAI News
Requests for Research 2.0
We’re releasing a new batch of seven unsolved problems which have come up in the course of our research at OpenAI.
Topics: Models
OpenAI News
Domain randomization and generative models for robotic grasping
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OpenAI News
OpenAI Baselines: ACKTR & A2C
We’re releasing two new OpenAI Baselines implementations: ACKTR and A2C. A2C is a synchronous, deterministic variant of Asynchronous Advantage Actor Critic (A3C) which we’ve found gives equal performance. ACKTR is a more sample-efficient reinforcement...
Topics: Models
OpenAI News
Proximal Policy Optimization
We’re releasing a new class of reinforcement learning algorithms, Proximal Policy Optimization (PPO), which perform comparably or better than state-of-the-art approaches while being much simpler to implement and tune. PPO has become the default...
OpenAI News
Learning from human preferences
One step towards building safe AI systems is to remove the need for humans to write goal functions, since using a simple proxy for a complex goal, or getting the complex goal a bit wrong, can lead to undesirable and even dangerous behavior. In collaboration...
Topics: Models
Entities: Models
OpenAI News
OpenAI Baselines: DQN
We’re open-sourcing OpenAI Baselines, our internal effort to reproduce reinforcement learning algorithms with performance on par with published results. We’ll release the algorithms over upcoming months; today’s release includes DQN and three of its variants.
Topics: Models