This paper revisits the temporal difference (TD) learning algorithm for the policy evaluation tasks in reinforcement learning. Typically, the performance of TD(0) and TD( λ ) is very sensitive to …
Dynamic multiobjective optimization problems (DMOPs) aim to optimize multiple (often conflicting) objectives that are changing over time. Recently, there are a number of promising algorithms propos…
Computer Vision, Feature Extraction, Image Recognition, Image Reconstruction, Image Representation, Image Sampling, Image Sensors, Learning Artificial Intelligence, Neural Nets, Object Detection, O…