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Authors: Paul McCarlie and Aaron Hunter

Affiliation: British Columbia Institute of Technology, 3700 Willingdon Avenue, Burnaby, Canada

Keyword(s): AI for Games, Rule-based Systems, Machine Learning.

Abstract: We explore the use of Artificial Intelligence (AI) to manipulate a simulated economy. Towards this end, we present work in progress on a macroeconomic simulation that can be controlled by a game player. We view this simulation as a sort of serious game; it can be played as a competition, but it can also be an educational tool through which players learn both about economic principles and the behaviour of AI controllers. The main contribution of this paper is the comparative study of the effectiveness of different AI agents for the manipulation of a simulated environment. Focusing on AI approaches that are common in the gaming industry, we implement four players that use intelligent methods to control the simulation by trying to maximize the economic output. The aim of our work is to illustrate that simple methods from the game AI community can be used to control a complex economic simulation effectively. This work, therefore, supports the common position in the gaming community that simple character-based AI methods can produce competitive game play even for complex tasks. Moreover, we demonstrate that, in the case of this particular simulation, a rule-based reasoner outperforms more sophisticated AI agents. (More)

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Paper citation in several formats:
McCarlie, P. and Hunter, A. (2021). Using Game AI to Control a Simulated Economy. In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-484-8; ISSN 2184-433X, SciTePress, pages 629-634. DOI: 10.5220/0010212306290634

@conference{icaart21,
author={Paul McCarlie. and Aaron Hunter.},
title={Using Game AI to Control a Simulated Economy},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2021},
pages={629-634},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010212306290634},
isbn={978-989-758-484-8},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - Using Game AI to Control a Simulated Economy
SN - 978-989-758-484-8
IS - 2184-433X
AU - McCarlie, P.
AU - Hunter, A.
PY - 2021
SP - 629
EP - 634
DO - 10.5220/0010212306290634
PB - SciTePress

- Science and Technology Publications, Lda.
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