An agent’s autonomy can be viewed as the set of physically and computationally grounded algorithms that can be performed by the agent. This view leads to two useful notions related to autonomy: behav- ior potential and success potential, which can be used to measure of how well an agent fulfills its potential, call fulfillment. Interaction algorithms enable multiple agents to coordinate, communicate, or exchange information. Short case studies are presented to illustrate how the algorithm-based definitions can be used to understand existing systems.
@inproceedings{goodrichetal21intellisys,
title={Autonomy Reconsidered: Toward Developing Multi-Agent Systems},
author={Michael Goodrich and Julie Adams and Matthias Scheutz},
year={2021},
booktitle={Proceedings of IntelliSys},
url={https://hrilab.tufts.edu/publications/goodrichetal21intellisys.pdf}
}