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As complex autonomous robotic systems become more widespread, the need fortransparent and reusable Artificial Intelligence (AI) designs becomes moreapparent. In this paper we analyse how the principles behind Behavior Trees(BTs), an increasingly popular tree-structured control architecture, areapplicable to these goals. Using structured programming as a guide, we analysethe BT principles of reactiveness and modularity in a formal framework ofaction selection. Proceeding from these principles, we review a number ofchallenging use cases of BTs in the literature, and show that reasoning viathese principles leads to compatible solutions. Extending these arguments, weintroduce 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 theaforementioned challenging BT use cases while preserving the BT principles.

A principled analysis of Behavior Trees and their generalisations