Neuroscience and Reinforcement Learning
#neuroscience #reinforcement_learning
https://www.princeton.edu/~yael/ICMLTutorial.pdf
#neuroscience #reinforcement_learning
https://www.princeton.edu/~yael/ICMLTutorial.pdf
Deep Learning and Computational Neuroscience
#neuroscience #reinforcement_learning
https://link.springer.com/article/10.1007/s12021-018-9360-6
#neuroscience #reinforcement_learning
https://link.springer.com/article/10.1007/s12021-018-9360-6
Neuroinformatics
Deep Learning and Computational Neuroscience
Neuroinformatics -
Solving Rubik’s Cube with a Robot Hand
This is fascinating, make sure you read it.
Summary: OpenAI team trained a pair of neural networks to solve the Rubik’s Cube with a human-like robot hand. The neural networks are trained entirely in simulation, using the same reinforcement learning code as OpenAI Five paired with a new technique called Automatic Domain Randomization (ADR). The system can handle situations it never saw during training, such as being prodded by a stuffed giraffe. This shows that reinforcement learning isn’t just a tool for virtual tasks, but can solve physical-world problems requiring unprecedented dexterity.
https://openai.com/blog/solving-rubiks-cube/
#reinforcement_learning #machine_learning #robotics
This is fascinating, make sure you read it.
Summary: OpenAI team trained a pair of neural networks to solve the Rubik’s Cube with a human-like robot hand. The neural networks are trained entirely in simulation, using the same reinforcement learning code as OpenAI Five paired with a new technique called Automatic Domain Randomization (ADR). The system can handle situations it never saw during training, such as being prodded by a stuffed giraffe. This shows that reinforcement learning isn’t just a tool for virtual tasks, but can solve physical-world problems requiring unprecedented dexterity.
https://openai.com/blog/solving-rubiks-cube/
#reinforcement_learning #machine_learning #robotics
Openai
Solving Rubik’s Cube with a robot hand
We’ve trained a pair of neural networks to solve the Rubik’s Cube with a human-like robot hand. The neural networks are trained entirely in simulation, using the same reinforcement learning code as OpenAI Five paired with a new technique called Automatic…
Proximal Policy Optimization
Paper:
https://openai.com/blog/openai-baselines-ppo/
YouTube Video:
https://www.youtube.com/watch?v=5P7I-xPq8u8&list=PLLO4N3-FoY3feUsA3_XZvn5sXy9Ms8ayE&index=2
#reinforcement_learning #optimization
Paper:
https://openai.com/blog/openai-baselines-ppo/
YouTube Video:
https://www.youtube.com/watch?v=5P7I-xPq8u8&list=PLLO4N3-FoY3feUsA3_XZvn5sXy9Ms8ayE&index=2
#reinforcement_learning #optimization
Openai
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 reinforcement…
PyTorch tutorial of various RL algorithms:
actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay
https://github.com/higgsfield/RL-Adventure-2
#reinforcement_learning #pytorch
actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay
https://github.com/higgsfield/RL-Adventure-2
#reinforcement_learning #pytorch
GitHub
GitHub - higgsfield-ai/higgsfield: Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed…
Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters - higgsfield-ai/higgsfield