Course Intermediate 10951
Course Introduction:"Self-study IT Network Linux Load Balancing Video Tutorial" mainly implements Linux load balancing by performing script operations on web, lvs and Linux under nagin.
Course Advanced 17019
Course Introduction:"Shangxuetang MySQL Video Tutorial" introduces you to the process from installing to using the MySQL database, and introduces the specific operations of each link in detail.
Course Advanced 10716
Course Introduction:"Brothers Band Front-end Example Display Video Tutorial" introduces examples of HTML5 and CSS3 technologies to everyone, so that everyone can become more proficient in using HTML5 and CSS3.
How to detach a Quasar Q card from the center?
2024-01-02 23:57:57 0 1 1065
Select rows in q-table via buttons using Vue.js
2023-09-02 16:25:14 0 1 540
Course Introduction:The Q function is a commonly used function in reinforcement learning and is used to calculate the expected cumulative return after an agent takes an action in a certain state. It plays an important role in reinforcement learning, helping agents learn optimal strategies to maximize expected returns. The calculation of the Q function is based on the interaction between the environment and the agent, and the strategy is optimized by continuously updating the Q value. Through continuous iteration, the agent can gradually learn the value of taking different actions in different states and choose the action with the highest Q value. In this way, the agent can make the optimal decision in any state to obtain the maximum return. In short, the Q function is one of the keys to realizing reinforcement learning. The Q function can be expressed as a mathematical formula: Q(s,a)=E[R_t+1+γR_t+2+γ^2R
2024-01-22 comment 0 998