Master Unreal Engine 5 AI Behavior Tree with this Tutorial

Master Unreal Engine 5 AI Behavior Tree with this Tutorial

Table of Contents:

1. Introduction
2. Setting Up the Character and Basic Blueprints
3. Understanding the Behavior Tree
4. Creating the Behavior Tree
5. Introduction to the Blackboard
6. Creating the Blackboard
7. Configuring the Behavior Tree and Blackboard
8. Composites: Selector, Sequence, and Simple Parallel
9. Creating Custom Tasks in the Behavior Tree
10. Adding a Random Location Task
11. Configuring the Random Location Task
12. Implementing the Behavior Tree in the AI Controller
13. Testing the Behavior Tree
14. Conclusion

Introduction

Welcome to part two of our UE5 AI tutorial series. In this episode, we will Delve deeper into the behavior tree system and explore its various functions. We will also learn how to Create custom tasks and use them to make our characters perform specific actions Based on decision making by the AI. So let's get started and learn how to make our AI characters more intelligent and dynamic.

Setting Up the Character and Basic Blueprints

Before we dive into the behavior tree system, it is essential to set up our character and the basic blueprints required for it. By doing so, we can ensure that our character is ready to utilize the behavioral systems provided by UE5. In this step, we will delete the existing character blueprint and replace it with a behavior tree. This will allow our character to have AI-controlled decision making capabilities. Let's create our first behavior tree named "NPC" and a blackboard named "BB_NPC" to enable communication between the tasks within the behavior tree.

Understanding the Behavior Tree

The behavior tree is a powerful system that governs the decision-making process of AI characters in UE5. It is designed as a top-down flow Chart, with various nodes representing different types of behaviors and actions. The behavior tree consists of composites, decorators, and tasks. Composites control the flow of execution, decorators add conditional logic, and tasks represent specific actions. In this section, we will focus on the different types of composites: selector, sequence, and simple parallel. We will explore their functionalities and how they affect the behavior of AI characters.

Creating the Behavior Tree

Creating a behavior tree is the first step in implementing AI decision making in UE5. A behavior tree consists of a root node and a series of interconnected nodes that define the logic and actions of the AI character. In this section, we will create our behavior tree named "NPC" and set up the initial structure using composites. We will also discuss the purpose of each composite and how they contribute to the overall behavior of the AI character.

Introduction to the Blackboard

The blackboard is an essential tool in UE5 that allows tasks within the behavior tree to communicate with each other and store shared information. It acts as a shared memory space for different AI-controlled characters. In this section, we will explore the concept of the blackboard and its role in enabling communication and data sharing among tasks within the behavior tree. We will also learn how to create a blackboard and configure it to work with our behavior tree.

Creating the Blackboard

To effectively use the blackboard in our behavior tree, we need to create a blackboard asset and set its properties. In this section, we will create a blackboard named "BB_NPC" and define the necessary variables to store and access information during runtime. We will also discuss the importance of correctly setting up the blackboard and ensure that it is correctly connected to the behavior tree.

Configuring the Behavior Tree and Blackboard

Once we have created the behavior tree and the blackboard, we need to configure them to work together seamlessly. In this section, we will explore the settings and properties of the behavior tree and the blackboard. We will discuss how to assign the blackboard asset to the behavior tree, set the initial values of blackboard variables, and ensure that the behavior tree is correctly linked to the blackboard.

Composites: Selector, Sequence, and Simple Parallel

Composites are key components of the behavior tree that control the flow of execution and dictate the order in which tasks are performed. In this section, we will focus on three types of composites: selector, sequence, and simple parallel. We will discuss their functionalities, use cases, and how they affect the decision-making process of AI characters. Additionally, we will examine the differences between these composites and learn when to use each one in our behavior tree.

Creating Custom Tasks in the Behavior Tree

Custom tasks allow us to define specific actions and behaviors for our AI characters within the behavior tree. In this section, we will learn how to create a custom task named "Move to Random Location" that makes the character run to a random location in the map. We will explore the different functions and parameters of custom tasks and understand how to implement their logic in the behavior tree.

Adding a Random Location Task

In this section, we will add the custom task "Move to Random Location" to our behavior tree. This task will enable our AI characters to dynamically select a random location in the map and move towards it. We will discuss the parameters and settings of the task and ensure that it is correctly integrated into the behavior tree.

Configuring the Random Location Task

To make the "Move to Random Location" task fully functional, we need to configure its parameters and behavior. In this section, we will set up the necessary variables, such as the radius for selecting random locations and the acceptance radius for determining when the character has reached its destination. We will also discuss the importance of these variables and how they impact the behavior of the AI character.

Implementing the Behavior Tree in the AI Controller

To make the behavior tree work in our game, we need to implement it in the AI controller class. In this section, we will go through the process of adding a "Run Behavior Tree" node to the AI controller's begin play event. This node will instruct the AI controller to execute the behavior tree we have created. By doing so, our AI character will start exhibiting the desired intelligent behavior based on the tasks defined in the behavior tree.

Testing the Behavior Tree

After implementing the behavior tree in the AI controller, it is crucial to test its functionality to ensure that it is working as intended. In this section, we will launch the game and observe the AI character's behavior as it runs to a random location in the map. We will verify that the behavior tree is executing the tasks correctly and that the character's movement is consistent with our expectations.

Conclusion

In this tutorial, we have explored the behavior tree system in UE5 and learned how to create custom tasks and configure them in the behavior tree. We have seen how the behavior tree facilitates decision making by AI characters and enables them to perform specific actions based on their Current state and the environment. By implementing the behavior tree in our game, we can create more intelligent and dynamic AI characters that enhance the player's experience.