The Octopus as a Model for Artificial Intelligence - A Multi-Agent Robotic Case Study

Alfonso Íñiguez

Abstract

The aim of this paper is to investigate the curious cognition process exhibited by the octopus, and its practical applicability to multi-agent systems. The paper begins by explaining the limitations of using the human brain as a model to achieve artificial cognition and proposes an alternative model inspired by the octopus’ distributed approach to solving problems. As a case study, a laboratory prototype demonstrates awareness, autonomy, solidarity, expandability, and resiliency in a multi-robotic system. The cognition model described in this paper is primarily algorithmic and does not explore the model creation process nor semantics; rather, it lays the foundation and inspiration for a future realization as a Process for Agent Societies Specification and Implementation (PASSI).

References

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Paper Citation


in Harvard Style

Íñiguez A. (2017). The Octopus as a Model for Artificial Intelligence - A Multi-Agent Robotic Case Study . In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-220-2, pages 439-444. DOI: 10.5220/0006125404390444


in Bibtex Style

@conference{icaart17,
author={Alfonso Íñiguez},
title={The Octopus as a Model for Artificial Intelligence - A Multi-Agent Robotic Case Study},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2017},
pages={439-444},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006125404390444},
isbn={978-989-758-220-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - The Octopus as a Model for Artificial Intelligence - A Multi-Agent Robotic Case Study
SN - 978-989-758-220-2
AU - Íñiguez A.
PY - 2017
SP - 439
EP - 444
DO - 10.5220/0006125404390444