Summary
In this chapter, we saw a new way – although experimental – to let your AI agents probe the level and gather information in order to make meaningful decisions.
Beginning with a bit of theory, we created an environment query, developed a fully operational behavior tree utilizing environment queries effectively, and tested it in a gym setting. Furthermore, we explored the use of debugging tools to analyze the activities within the level.
This concludes Part 3 of this book. In the upcoming chapters, we will delve into new features within the AI framework, beginning with a glimpse at an alternative method of implementing AI agents: hierarchical state machines.
