Distributional Q-learning is a modern approach in reinforcement learning that extends traditional Q-learning by focusing on the distribution of future rewards rather than simply estimating their expected value. Unlike conventional Q-learning, which predicts the average reward for a given action in a particular state, distributional Q-learning models the entire probability distribution of possible outcomes. This … Read more
Class incremental learning is an important concept in modern machine learning that focuses on how models can learn new classes of data over time without forgetting what they have already learned. In traditional machine learning, models are usually trained on a fixed dataset that includes all classes at once. However, in real-world applications, new categories … Read more
Learning resources in gemology crystal labs play an important role for anyone interested in studying gemstones, minerals, and crystals in a structured and scientific way. Gemology is the study of precious and semi-precious stones, and crystal laboratories provide the practical environment where learners can observe, test, and analyze real samples. These learning resources help students, … Read more