A Behavior Tree-inspired programming language for autonomous agents

TL;DR

This paper introduces a new functional programming language inspired by Behavior Trees for autonomous agents, addressing limitations of traditional BTs and enhancing modularity and reactivity.

Contribution

It extends the Behavior Tree model into a full programming language with primitives for modularity, reactivity, and safety, implemented in Haskell.

Findings

Demonstrates handling of complex agent behaviors with the new language

Provides a formal specification and implementation in Haskell

Successfully translates complex BTs into unambiguous programs

Abstract

We propose a design for a functional programming language for autonomous agents, built off the ideas and motivations of Behavior Trees (BTs). BTs are a popular model for designing agents behavior in robotics and AI. However, as their growth has increased dramatically, the simple model of BTs has come to be limiting. There is a growing push to increase the functionality of BTs, with the end goal of BTs evolving into a programming language in their own right, centred around the defining BT properties of modularity and reactiveness. In this paper, we examine how the BT model must be extended in order to grow into such a language. We identify some fundamental problems which must be solved: implementing `reactive' selection, 'monitoring' safety-critical conditions, and passing data between actions. We provide a variety of small examples which demonstrate that these problems are complex, and that current BT approaches do not handle them in a manner consistent with modularity. We instead provide a simple set of modular programming primitives for handling these use cases, and show how they can be combined to build complex programs. We present a full specification for our BT-inspired language, and give an implementation in the functional programming language Haskell. Finally, we demonstrate our language by translating a large and complex BT into a simple, unambiguous program.