Reinforcement learning focuses on rewarding desired AI actions and punishing undesired ones. Common RL algorithms include State-action-reward-state-action, Q-learning, and Deep-Q networks. RL adapts ...

The battle at OpenAI was possibly due to a massive breakthrough dubbed Q* (Q-learning). Q* is a precursor to AGI. What Q* might have done is bridged a big gap between Q-learning and pre-determined ...

We set out to create a single algorithm that would be able to develop a wide range of competencies on a varied range of challenging tasks—a central goal of general artificial intelligence 13 that has ...

These days, artificial intelligence developers, investors and founders are all obsessed with “reinforcement learning,” a ...

Reinforcement learning (RL) is a branch of machine learning that addresses problems where there is no explicit training data. Q-learning is an algorithm that can be used to solve some types of RL ...

David Silver of Google DeepMind thinks AIs that ‘learn by experience’ are the future of AI – but maybe not in particle ...

Reinforcement learning (RL) is a type of machine learning where an agent learns to make decisions by interacting with an environment. Think of it like training a dog: every time the dog sits on ...