论文标题
对行为树及其概括的原则分析
A principled analysis of Behavior Trees and their generalisations
论文作者
论文摘要
随着复杂的自主机器人系统变得更加普遍，对透明和可重复使用的人工智能（AI）设计的需求变得越来越明显。在本文中，我们分析了行为树（BTS）背后的原理如何适用于这些目标。使用结构化编程作为指导，我们在正式的动作选择框架中分析了BT反应性和模块化原则。从这些原则开始，我们回顾了文献中BTS的许多挑战性用例，并表明通过这些原则进行推理会导致兼容解决方案。扩展这些论点，我们引入了一种新的控制架构类别，我们称为广义BTS或$ K $ -BTS，并展示它们如何扩展BTS在保留BT原理的同时，将BTS的适用性扩展到上述一些挑战的BT用例中。
As complex autonomous robotic systems become more widespread, the need for transparent and reusable Artificial Intelligence (AI) designs becomes more apparent. In this paper we analyse how the principles behind Behavior Trees (BTs), an increasingly popular tree-structured control architecture, are applicable to these goals. Using structured programming as a guide, we analyse the BT principles of reactiveness and modularity in a formal framework of action selection. Proceeding from these principles, we review a number of challenging use cases of BTs in the literature, and show that reasoning via these principles leads to compatible solutions. Extending these arguments, we introduce a new class of control architectures we call generalised BTs or $k$-BTs and show how they can extend the applicability of BTs to some of the aforementioned challenging BT use cases while preserving the BT principles.
