Trading Agent Competition with Autonomous Economic Agents

David Minarsch, Seyed Ali Hosseini, Marco Favorito, Marco Favorito, Jonathan Ward

2021

Abstract

We provide a case study for the Autonomous Economic Agent (AEA) framework; a toolkit for the development and deployment of autonomous agents with a focus on economic activities. The use case is the trading agent competition (TAC). It is a competition between autonomous agents with customisable strategies and market parameters. The competition is facilitated by the AEA framework’s native support for decentralised ledger technologies, i.e. permissionless blockchains and smart contract functionality, for immutable transaction recording and trade settlement. We provide an open-source implementation, study the result of the competitions we ran, and compare it to theoretical results in the economics literature. We conclude by discussing its real-world applications in crypto-currency, digital assets and token trading.

Paper Citation

in Harvard Style

Minarsch D., Hosseini S., Favorito M. and Ward J. (2021). Trading Agent Competition with Autonomous Economic Agents.In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 1: SDMIS, ISBN 978-989-758-484-8, pages 574-582. DOI: 10.5220/0010431805740582

in Bibtex Style

@conference{sdmis21,
author={David Minarsch and Seyed Ali Hosseini and Marco Favorito and Jonathan Ward},
title={Trading Agent Competition with Autonomous Economic Agents},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 1: SDMIS,},
year={2021},
pages={574-582},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010431805740582},
isbn={978-989-758-484-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 1: SDMIS,
TI - Trading Agent Competition with Autonomous Economic Agents
SN - 978-989-758-484-8
AU - Minarsch D.
AU - Hosseini S.
AU - Favorito M.
AU - Ward J.
PY - 2021
SP - 574
EP - 582
DO - 10.5220/0010431805740582