TD(0) is one of TD learning method which considers only the next state, yet TD(1) is the other kind of TD learning which take the accumulated reward of the following states in the account. TD(1) is the well-known Monte-Carlo method. The difference between them is the target in evaluation function:

Knowledge is accumulated based on numbers and text. Each number represents the outcome of the observed event. Extract the information among numbers and estimated the randomness behind events are methods to gather knowledge. Based on probability, which describes randomness, Statistics is a collection of approaches that provides summaries and inferences. According to different utilizations on probability, two main schools are developed: Frequentist Statistics and Bayesian Statistics.

According to the article “top performers over the past 24 hours” in website World Markets Snapshot, there are 2 key points mentioned. In the first paragraph, the author summarizes the numbers in the category by averaging. Then, the individual stock performance followed. However, it is hard to tell the key points in the current version chart that is shown above. The 2 key points are: