AI-Driven Approaches in Reinforcement and Supervised Learning

Keywords: Reinforcement Learning, Supervised Learning, Neural Networks, Machine Learning, Reproducibility

TL;DR: We propose hybrid AI approaches combining supervised learning and reinforcement learning to improve accuracy, interpretability, and reproducibility.

Abstract: This paper presents approaches to AI-driven research in reinforcement learning and supervised learning tasks. We explore methods combining neural networks and classical machine learning algorithms to predict outcomes and optimize performance. Experiments demonstrate how AI techniques can be leveraged for reproducible, accurate, and interpretable results. Our study emphasizes methodological transparency and highlights potential limitations for future work.

Submission Number: 222