Design of Intelligent System for Puzzle Games Based on Machine Learning

In terms of data processing in puzzle games, this research paper studies and implements a set of data table workflows, with the aim of improving the flexibility of data configuration and increasing the convenience of data export, runtime loading, and data usage. This article implements a puzzle game framework that encapsulates the underlying modules and provides support for the upper logic modules. The three most important and commonly used modules in game frameworks are: state machine module, resource management module, and log module. The research results indicate that based on the puzzle game framework, the development efficiency of logical functions has been greatly improved, and the portability of the code has been greatly enhanced. Through overall testing, it can be seen from the overall performance that the game client is running well, and all parts meet the expected requirements. It also meets the requirements in non-functional aspects such as performance.