Hierarchical Task Network Planning AI

Create AI that can plan ahead using this flexible, fully-featured alternative to Behavior Trees

The HTN Planning plugin lets you create AI that can plan multiple steps ahead by predicting the consequences of its actions.

Hierarchical Task Network (HTN) planning is a powerful artificial intelligence technique that allows for the efficient and effective planning of complex tasks in video games and other applications. With the rising popularity of virtual and augmented reality experiences, game developers are constantly seeking ways to enhance the realism and immersion in their games. This is where the HTN planning AI unreal engine asset comes into play. This asset uses a hierarchical structure to break down complex tasks into smaller, more manageable subtasks, allowing for more efficient and flexible planning. This is especially useful in game development, where there are often many different tasks that need to be completed simultaneously, such as character movement, enemy behavior, and object interactions. The HTN planning AI unreal engine asset allows developers to easily define and prioritize these tasks, resulting in more realistic and dynamic gameplay. Additionally, the hierarchical structure of HTN planning allows for easy modification and adaptation of tasks, making it an ideal choice for games with constantly changing environments or player choices. With the help of this asset, game developers can create more immersive and engaging experiences for players, making their games stand out in a competitive market. Furthermore, the use of HTN planning AI can also improve the overall performance and efficiency of games, as it allows for better resource management and decision-making. In conclusion, the HTN planning AI unreal engine asset is a valuable tool for game developers, providing them with the means to create more realistic, dynamic, and efficient gameplay experiences.

Just like with Behavior Trees, you can easily create Tasks, Decorators, and Services from either C++ or Blueprints, and arrange them in a visual graph editor. The HTN planner uses Blackboard data to store knowledge about possible future worldstates. Nodes check and modify values in the worldstate during planning, which makes it possible to make decisions based on possible future states. The planner efficiently finds the plan with the lowest cost, or the one with the highest priority.

Compared to other planning techniques like Goal-Oriented Action Planning, HTN planning is more efficient and gives designers much more control over the AI. It can be as rigid as Behavior Trees, or as flexible as GOAP. You can create AI with just as much autonomy and flexibility as you need: an AI that selects between predefined sequences of tasks, or an AI that is free to arrange its tasks in any order to achieve a goal, or anything in between.

Version 1.12.1

Features:

• Node-based HTN graph editor
• Seamlessly use Blackboard data as worldstate
• Make custom Tasks, Decorators, and Services in both C++ and Blueprints
• Create composable behaviors using subnetworks
• Make subplans within plans to freely mix planning and on-the-fly decision-making
• Cost-based or priority-based planning
• Parallel planning
• Any-order planning
• Integration with the Visual Logger, including visualizing the current plan
• Integration with the Environment Query System for complex movement planning and decision-making
• Realtime debugging features
• Extend the HTN Component with HTN Extensions
• Full source code access

For more info, check out the documentation website, the tutorials, and the official Discord community.

Technical Details

Code Modules:

• HTN [Runtime]
• HTNEditor [Editor]

Number of Blueprints: 0

Number of C++ Classes: 70

Network Replicated: No (not needed for AI)

Supported Development Platforms: Windows, macOS, Linux

Supported Target Build Platforms: Windows 64-bit, macOS, Linux, Android, iOS