# Hidden Markov Models derived from Behavior Trees

arXiv: https://arxiv.org/abs/1907.10029 · HTML: https://mlsanity.com/paper/1907.10029/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Jul 2019.

## Built on by (most cited first, 1 of 1)

- [An expressiveness hierarchy of Behavior Trees and related architectures](https://mlsanity.com/paper/2104.07919/) (2021)

## Abstract (arXiv)

Behavior trees are rapidly attracting interest in robotics and human task-related motion tracking. However no algorithms currently exist to track or identify parameters of BTs under noisy observations. We report a new relationship between BTs, augmented with statistical information, and Hidden Markov Models. Exploiting this relationship will allow application of many algorithms for HMMs (and dynamic Bayesian networks) to data acquired from BT-based systems.