Kalman Optimization for Value Approximation

KOVA: Addressing Uncertainties in Deep Reinforcement Learning If you're interested in artificial intelligence (AI) and machine learning, you might have heard of deep reinforcement learning (RL). This subfield of AI focuses on training agents to make decisions based on rewards, and it has led to impressive results in various domains, from playing Atari games to controlling robots. However, deep RL also faces some challenges, one of which is dealing with uncertainties. In deep RL, an agent typic