Hierarchical Task Network Planning AI 1.7.2 虚幻4.27

支持引擎版本4.27

The HTN Planning plugin lets you create AI that can plan multiple steps ahead by predicting the consequences of its actions. Here are some examples:
Video: an HTN-based character inventing the optimal plan to attack a target
Video: two groups of HTN-based characters tactically fighting in a simple FPS arena

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.

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


HTN Planning插件允许你创建AI，它可以通过预测其行为的后果来提前计划多个步骤。下面是一些例子:
视频:一个基于html的角色发明了攻击目标的最佳计划
视频:两组基于html的角色在一个简单的FPS舞台上进行战术战斗

就像行为树一样，你可以很容易地从c++或蓝图中创建任务、装饰器和服务，并将它们安排在一个可视化的图形编辑器中。HTN规划器使用Blackboard数据来存储关于未来可能的世界状态的知识。节点在规划期间检查和修改worldstate中的值，这使得基于可能的未来状态做出决策成为可能。计划者可以有效地找到成本最低或优先级最高的计划。

与其他计划技术(如目标导向行动计划)相比，HTN计划更有效，并让设计师能够更好地控制AI。它可以像行为树一样严格，也可以像GOAP一样灵活。你可以根据自己的需要创造具有自主权和灵活性的AI:可以在预定义的任务序列之间进行选择的AI，或者可以自由安排任务以实现目标的AI，或者介于两者之间的AI。

特点:
基于节点的HTN图形编辑器
无缝地使用Blackboard数据作为worldstate
在c++和蓝图中创建自定义任务、装饰器和服务
使用子网创建可组合的行为
在计划中制定子计划，将计划和即时决策自由地结合起来
基于成本或优先级的计划
并行规划
任何顺序规划
与可视化日志记录器集成，包括可视化当前计划
与环境查询系统集成，用于复杂的运动规划和决策
实时调试特性
用HTN Extensions扩展HTN组件
完整的源代码访问

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