Behavior trees (BTs) emerged from video game development as a graphical language for modeling intelligent agent behavior. BTs have several properties which are attractive for modeling medical procedures including human-readability, authoring tools, and composability. This paper will illustrate construction of BTs for exemplary medical procedures 1 . Prior to about 2010, the term Behavior Tree (BT) was used idiosyncratically by several authors, but around that time a literature began to emerge around a tree model of behaviors used by the game industry for AI-based characters [1, 2] . These BTs assume that units of intelligent behavior (such as sensing procedures or sense/action pairs) can be programmed such that they perform a piece of an overall task/behavior, and that they can determine and return a 1-bit result indicating success or failure. These units are the leaves of BTs. The level of abstraction of BT leaves is not specified by the BT formalism and varies from one application to another. In the context of medical robotics, they could be things such as a guarded move, a precision cutting action, acquisition of an ultrasound image, creation of a plan, etc. Earlier medical robotics systems such as Robodoc addressed the problem with, for example, scripting languages [3] . Recent literature has applied BTs to UAV control[4], humanoid robotic control[5], and human-robot cooperation in manufacturing[6]. Theoretical classification of BTs has been studied by several authors[7] which has formally related BTs to Finite State Machines (FSMs). BTs have advantages of modularity and scalability with respect to finite state machines. Other theoretical studies have related BTs to Hybrid Dynamical Systems[8], humanoid robotic behavior[5], and derivation of correctness guarantees[9]. Software packages and ROS implementations 2 are now available[10]. Several of the above references have ample introductory material and examples of BT concepts. When implementing intelligent behavior with BTs, the designer of a robotic control system breaks the task down into modules (BT leaves) which return either "success" or "failure" when called by parent nodes. All higher level nodes define composition rules to combine the leaves including: Sequence, Selector, and Parallel node types. A Sequence node defines the order of execution of leaves and returns success if all leaves succeed in order. A Selector node (also called "Priority" node by some authors) tries leaf behaviors in a fixed order, returning success when a node succeeds, and failure if all leaves fail. Decorator nodes have a single child and can modify behavior of their children with rules such as "repeat until X > 0". BTs have been explored in the context of humanoid robot control [10, 11, 12] and as a modeling language for intelligent robotic surgical procedures [13] . In this paper, we explore the use of BTs to represent medical procedures (often referred to as algorithms). We will illustrate this use by converting published algorithms given in the literature to BTs.
A more recent work REF uses BTs to represent medical procedures.
Behavior Trees as a Representation for Medical Procedures
ArXiv
ArXiv
Computer Science