How to Implement Artificial Intelligence in Unreal Engine

Edited 4 weeks ago by ExtremeHow Editorial Team

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Artificial intelligence (AI) plays a vital role in modern video games, offering players the thrill of competing against credible, intelligent opponents. Unreal Engine, a robust and popular game engine, provides extensive tools and systems for integrating AI into your gaming project. Implementing AI within Unreal Engine involves understanding and using several essential components such as behavior trees, AI controllers, navigation meshes, and blackboards. In this article, we will delve into an easy-to-follow guide to implementing artificial intelligence using these tools within Unreal Engine.

An introduction to Unreal Engine's AI system

The Unreal Engine is renowned for its user-friendly interface, powerful graphical capabilities, and a wide range of development tools. AI in the Unreal Engine basically revolves around the behavior tree system, which allows developers to design complex decision-making processes for non-player characters (NPCs). Combined with AI controllers and other supporting systems, developers can create detailed and interactive AI agents.

Set up your project

Before implementing AI, it's important to set up your project correctly in Unreal Engine. Here's a step-by-step guide to preparing your environment:

1. Create a new project: Open Unreal Engine and create a new game project. Choose the template that best suits your game type and make sure you select C++ if you want to go deeper into custom scripting.
2. Basic setup for AI: Make sure you have basic game elements such as scenarios or a simple level setup so you can effectively test your AI components. Having characters or antagonists will also be helpful.

Understanding AI Components

Unreal Engine's AI system is made up of many parts that work together to produce intelligent behavior. Below are the main components you'll be working with:

AI Controller

AI controllers are important parts of the AI system in Unreal Engine. They use player input or decision-making processes to control non-player characters.

To implement an AI controller:

1. Create a new C++ class derived from AAIController. This will be your AI controller.
2. Override the function as needed. You may want to use OnPossess() function to set up your pawn (the character being controlled) and initialize your AI strategies.

class MyAIController : public AAIController { // Constructor MyAIController(); // Called when the controller possesses a pawn void OnPossess(APawn* InPawn) override; };

Behavior Tree

Behavior trees are used to create modular and complex decision trees for character behavior. They provide a graphical way to design the logic behind AI decisions.

Steps to create a behavior tree:

1. In the Content Browser, right-click and select Create Asset > Artificial Intelligence > Behavior Tree
2. Define behavior by adding nodes to the tree. Composite nodes determine the flow of decisions, while decorator nodes handle conditional checks and service nodes provide continuation logic.

Blackboard

The blackboard acts as a data repository in conjunction with the behavior trees, and stores important data that the tree nodes can access.

1. Create a new blackboard under Create Asset > Artificial Intelligence > Blackboard.
2. Add keys to represent game data elements, such as patrol points, player references, or booleans to represent states.

Navigation Mesh

The navigation mesh (navmesh) defines the walkable areas within your game world, allowing AI-controlled characters to move around freely and naturally.

1. Place a NavMeshBoundsVolume in your level to define the area the AI can navigate.
2. Press P key to view the navigation mesh. Areas highlighted in green are walkable.

Implementing AI: Bringing it together

Once you have the different components set up, it’s time to integrate and implement the AI within Unreal Engine:

Step 1: Setting up the AI Controller

Assign an AI controller to your NPC character: In the Details panel of your character blueprint, under Pawn section, set AI Controller Class for your custom AI controller.

Step 2: Defining behavior with behavior trees

Open your behavior tree and start defining a sequence of behaviors.

• Use Selector nodes to determine which actions to perform based on conditions.
• Create functions for movements or actions, such as MoveTo functions, allowing your NPC to move to target locations set in the blackboard.
• Use Decorator nodes for logic checks, such as determining if an enemy is in sight or has health below a certain threshold.

Step 3: Data Management with Blackboard

Implement logic to update the blackboard with game world data. In your AI controller script:

void MyAIController::BeginPlay() { // Obtain the blackboard component UseBlackboard(BlackboardComponent, BlackboardAsset); // Set initial blackboard values BlackboardComponent->SetValueAsVector(TEXT("HomeLocation"), GetPawn()->GetActorLocation()); }

Step 4: Working with Navigation

Make sure your AI character can navigate the environment using the NavMesh you set up earlier. Check if the character's movement component is properly configured.

Step 5: Test and Iterate

After setting up your AI, it's important to test it within the level to ensure that behaviors are executing as intended. Debugging tools and logs can be invaluable here.

Optimizing AI performance

When implementing AI into your game, performance optimization becomes extremely important, especially in large or complex scenes where many AI characters are active. Here are some guidelines for increasing efficiency:

• Adjust the navigation mesh: Limit the extent and complexity of your navigation mesh to the areas necessary for navigation.
• Efficient use of Blackboard: Make sure you are storing only the data that is necessary to make a decision.
• Use simple logic: Start with simple logic and gradually increase the complexity as needed.

Advanced topics

Once you’re comfortable with the basic AI features, you can explore advanced integrations:

Environmental Query System (EQS)

EQS can enhance AI by providing them environmental data to make better decisions. Queries can determine paths, target locations, and analyze surrounding elements.

Machine Learning Integration

Integrate machine learning components to develop AI's decision-making processes. Unreal Engine supports third-party plugins and APIs to leverage machine learning capabilities.

Custom C++ functions

Create complex AI tasks and nodes using C++ to precisely define behavioral actions or modify existing functions for specific logic flows.

Conclusion

Implementing AI in the Unreal Engine involves linking together various systems such as the AI controller, behavior tree, blackboard, and navigation mesh. Each plays a unique role, and together they enable the creation of sophisticated behaviors required for modern gaming. Constant testing and iteration, along with performance optimization, are essential to ensure that both the functionality and enjoyment of the game are maintained. By following this guide and exploring advanced techniques, you can develop intelligent and engaging NPCs, taking your game project to new levels.

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