Teaching AI to explore its surroundings is a bit like teaching a robot to find treasure in a vast maze—it needs to try different paths, but some lead nowhere. In many real-world challenges, like ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

Researchers have identified peptides that can help remove microplastics from the environment by combining biophysical modeling, molecular dynamics, quantum computing, and reinforcement learning.

Learn More OpenAI today announced on its developer-focused account on the social network X that third-party software developers outside the company can now access reinforcement fine-tuning (RFT ...

Machine learning and artificial intelligence are fundamentally dependent on databases. These databases serve the vital role of storing, organizing, and pulling up necessary data to develop and ...

Are you wondering what’s next? To many, the future of technology lies squarely with machine learning and with artificial intelligence, known as AI. Artificial intelligence refers to technologies that ...

The authors present a biologically plausible framework for action selection and learning in the striatum that is a fundamental advance in our understanding of possible neural implementations of ...

Abstract: This paper proposes a novel hierarchical reinforcement learning (HRL) framework of complex manipulation tasks which integrates the human prior knowledge. The framework involves the following ...