A Resourceful Reframing of Behavior Trees
This work addresses the problem of designing scalable and reusable autonomous behaviors for agents in games and virtual environments, representing an incremental improvement through formalization.
The paper tackled the challenges of scalability, reasoning, and reuse in Behavior Trees used for autonomous agents by presenting a formal alternative with operational semantics and a type system based on linear logic. The result was a framework that enables compositional reasoning and reuse of behavior building blocks through type assignments.
Designers of autonomous agents, whether in physical or virtual environments, need to express nondeterminisim, failure, and parallelism in behaviors, as well as accounting for synchronous coordination between agents. Behavior Trees are a semi-formalism deployed widely for this purpose in the games industry, but with challenges to scalability, reasoning, and reuse of common sub-behaviors. We present an alternative formulation of behavior trees through a language design perspective, giving a formal operational semantics, type system, and corresponding implementation. We express specifications for atomic behaviors as linear logic formulas describing how they transform the environment, and our type system uses linear sequent calculus to derive a compositional type assignment to behavior tree expressions. These types expose the conditions required for behaviors to succeed and allow abstraction over parameters to behaviors, enabling the development of behavior "building blocks" amenable to compositional reasoning and reuse.