Artificial Intelligence in Game Development: Understanding Behavior Trees

Introduction

In the wild world of videogames, you'll inevitably encounter a foe that needs to be both engaging and captivating. This opponent isn't just a bunch of nice-to-see polygons and textures; it needs to be a challenge that'll keep your players hooked to the screen.

Let's be honest, as a game developer, crafting a truly engaging opponent is often a challenge that rivals the one your players will face!

In video games, we often use the term Artificial Intelligence (AI) to describe characters that are not controlled by the player, whether they are enemies or friendly entities. There are countless ways to develop compelling characters in video games. In this article, we'll explore one specific solution offered by Unreal Engine: behavior trees.

Note

Citations come from my Artificial Intelligence in Unreal Engine 5 book.

Using the Unreal Shooting Gym Project

For this article, I have created a dedicated project called Unreal Shooting Gym. You can freely download it from GitHub: https://github.com/marcosecchi/unreal-shooting-gym and open it up with Unreal Engine 5.4.

Once opened, you should see a level showing a lab with a set of targets and a small robot armed with a gun (A.K.A. RoboGun), as shown in Figure 1:

Figure 1. The project level.

If you hit the Play button, you should notice the RoboGun rotating toward a target while shooting. Once the target has been hit, the RoboGun will start rotating towards another one. All this logic has been achieved through a behavior tree, so let’s see what it is all about.

Behavior Trees

“In the universe of game development, behavior trees are hierarchical structures that govern the decision-making processes of AI characters, determining their actions and reactions during gameplay.”

Unreal Engine offers a solid framework for handling behavior trees based on two main elements: the blackboard and behavior tree assets.

Blackboard Asset

“In Unreal Engine, the Blackboard [...] acts as a memory space – some sort of brain – where AI agents can read and write data during their decision-making process.“

By opening the AI project folder, you can double-click the BB_Robogun asset to open it. You will be presented with the blackboard that, as you can see from Figure 2, is quite simple to understand.

Figure 2. The AI blackboard

As you can see there’s a couple of variables – called keys – that are used to store a reference to the actor owning the behavior tree – in this case, the RoboGun – and to the target object that will be used to rotate the RoboGun.

Behavior Tree Asset

“In Unreal Engine, behavior trees are assets that are edited in a similar way to Blueprints – that is, visually – by adding and linking a set of nodes with specific functionalities to form a behavior tree graph.”

Now, double-click the BT_RoboGun asset located in the AI folder to open the behavior tree. You should see the tree structure depicted in Figure 3:

Figure 3. The AI behavior tree

Although this is a pretty simple behavior logic, there’s a lot of things involved here. First of all, you will notice that there is a Root node; this is where the behavior logic starts from.

After that, you will see that there are three gray-colored nodes; these are defined composite nodes.

“Composite nodes define the root of a branch and set the rules for its execution.”

Each of them behaves differently, but it is sufficient to say that they control the subtree that will be executed; as an example, the Shoot Sequence node will execute all the subtrees one after the other.

The purple-colored nodes are called tasks and they are basically the leaves of the tree, whose aim is to execute actions. Unreal Engine comes with some predefined tasks, but you will be able to create your own through Blueprints or C++.

As an example, consider the Shoot task depicted in Figure 4: 

Figure 4. The Shoot task

 In this Blueprint, when the task is executed, it will call the Shoot method – by means of a ShootInterface – and then end the execution with success. For a slightly more complex task, please check the  BTTask_SeekTarget asset.

Get back to the behavior tree, and you will notice that the Find Random Target node has a blue-colored section called Is Target Set? This is a decorator. 

“Decorators provide a way to add additional functionality or conditions to the execution of a portion of a behavior tree.”

In our case, the decorator is checking if the TargetActor blackboard key is not set; the corresponding task will be executed only if that key is not set – that is, we have no viable target. If the target is set, this decorator will block task execution and the parent selector node – the Root Selector node – will execute the next subtree.

Environment Queries

Unreal Engine provides an Environment Query System (EQS) framework that allows data collection about the virtual environment. AI agents will be able to make informed decisions based on the results.

In our behavior tree, we are running an environment query to find a viable target in the Find Random Target task. The query I have created – called EQ_FindTarget – is pretty simple as it just queries the environment looking for instances of the class BP_Target, as shown in Figure 5:

Figure 5. The environment query

Pawn and Controller

Once you have created your behavior tree, you will need to execute it through an AIController, the class that is used to possess pawns or characters in order to make them proper AI agents. In the Blueprints folder, you can double-click on the RoboGunController asset to check the pretty self-explanatory code depicted in Figure 6:

Figure 6. The character controller code

As you can see, it’s just a matter of running a behavior tree asset. Easy, isn’t it?

If you open the BP_RoboGun asset, you will notice that, in the Details panel, I have set the AI Controller Class to the RoboGunController; this will make the RoboGun pawn be automatically possessed by the RoboGunController.

Conclusion

This concludes this brief overview of the behavior tree system; I encourage you to explore the possibilities and more advanced features – such as writing your code the C++ way – by reading my new book “Artificial Intelligence in Unreal Engine 5”; I promise you it will be an informative and, sometimes, funny journey!

Author Bio

Marco Secchi is a freelance game programmer who graduated in Computer Engineering at the Polytechnic University of Milan. He is currently lecturer of the BA in Creative Technologies and of the MA in Creative Media Production. He also mentors BA students in their final thesis projects. In his spare time, he reads (a lot), plays (less than he would like) and practices (to some extent) Crossfit.