Archives for offline reinforcement learning
The success of deep learning has been linked to how well the algorithms generalised when presented with open-world settings. This notion transformed the fields of computer vision and natural language processing. Reinforcement learning, on the other hand, has been playing catch up within realms of AI. The potential is immense. But, applying RL is not…
The post Researchers Introduce A New Algorithm For Faster Reinforcement Learning appeared first on Analytics India Magazine.
Recently, researchers from DeepMind and Google introduced methods for choosing the best policy in offline reinforcement learning (ORL) known as offline hyperparameter selection (OHS). It uses logged data from a set of many policies that are trained using different hyperparameters. Reinforcement learning has become one of the most critical techniques in AI which has been…
The post DeepMind & Its Parent Company Google Are Betting Big On Reinforcement Learning appeared first on Analytics India Magazine.
Reinforcement learning is one of the most important techniques used to achieve artificial general intelligence. However, it has various disadvantages that prevent researchers from achieving true AI. Since AI agents are trained to learn by hit and trial method, providing every possible real-world circumstance is a huge challenge. The world is yet to address these…
The post How To Address Offline Reinforcement Learning Challenges appeared first on Analytics India Magazine.