Complex robot behaviour typically requires the integration of multiple robotic and Artificial Intelligence (AI) techniques and components. Integrating such disparate components into a coherent system, while also ensuring global properties and behaviours, is a significant challenge for cognitive robotics. Using a formal framework to model the interactions between components can be an important step in dealing with this challenge. In this paper we extend an existing formal framework [Clark et al., 2016] to model complex integrated reasoning behaviours of robotic systems; from symbolic planning through to online learning of policies and transition systems. Furthermore the new framework allows for a more flexible modelling of the interactions between different reasoning components.
@article{arxiv.2310.12386,
title = {Online Learning and Planning in Cognitive Hierarchies},
author = {Bernhard Hengst and Maurice Pagnucco and David Rajaratnam and Claude Sammut and Michael Thielscher},
journal= {arXiv preprint arXiv:2310.12386},
year = {2023}
}