arXiv · 1907.10029
Hidden Markov Models derived from Behavior Trees
Abstract
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.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Blake Hannaford. 2019-07-23. Hidden Markov Models derived from Behavior Trees. https://arxiv.org/abs/1907.10029
Cite the original work for its findings. Save a collection to share your selection of sources.