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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. Easily use the Blackboard to store knowledge about possible futures and modify it from within graph nodes. 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. You can create AI with just as much autonomy and flexibility as you need.
Features:
Node-based HTN graph editor
Seamlessly use Blackboard data as worldstate
Make custom Tasks, Decorators, and Services in both C++ and Blueprints
Cost-based or priority-based planning.
Parallel planning
Any-order planning
Visualize the current plan of any AI via the Visual Logger
Integration with the Environment Query System for complex movement planning and decision-making
Realtime debugging features
就像使用行为树一样，您可以从C++或蓝图中轻松创建任务、装饰器和服务，并在可视化图形编辑器中排列它们。轻松使用黑板存储有关可能未来的知识，并在图节点内对其进行修改。规划者有效地找到成本最低或优先级最高的计划。
与其他规划技术（如目标导向行动规划）相比，HTN规划更高效，让设计师对人工智能有更多的控制权。你可以根据需要创建具有自主性和灵活性的人工智能。
特征：
基于节点的HTN图形编辑器
无缝使用Blackboard数据作为世界状态
在C++和蓝图中创建自定义任务、装饰器和服务
基于成本或基于优先级的规划。
平行规划
任何订单计划
通过可视化记录器可视化任何AI的当前计划
与环境查询系统集成，用于复杂的运动规划和决策
实时调试功能
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