Reinforcement Learning

Abstract

Through the application of reinforcement learning, neural networks have now developed the capability to make sequential decisions based on trial and error within an environment that provides rewards. This method is analogous to the training process of domestic pets, but applied within the domain of artificial intelligence. These neural networks have achieved a level of comprehension of the surrounding environment, allowing them to engage in informed actions. The forthcoming lecture will delve into the potential significance of neural network training in future contexts, and will highlight the remarkable discoveries and advancements made in this field over the past few years.