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Can we replicate real human behaviour using artificial neural networks?
- Source :
- Mathematical & Computer Modelling of Dynamical Systems; Dec2022, Vol. 28 Issue 1, p95-109, 15p
- Publication Year :
- 2022
-
Abstract
- Agent-based modelling is a powerful tool when simulating human systems, yet when human behaviour cannot be described by simple rules or maximizing one's own profit, we quickly reach the limits of this methodology. Machine learning has the potential to bridge this gap by providing a link between what people observe and how they act in order to reach their goal. In this paper we use a framework for agent-based modelling that utilizes human values like fairness, conformity and altruism. Using this framework we simulate a public goods game and compare to experimental results. We can report good agreement between simulation and experiment and furthermore find that the presented framework outperforms strict reinforcement learning. Both the framework and the utility function are generic enough that they can be used for arbitrary systems, which makes this method a promising candidate for a foundation of a universal agent-based model. [ABSTRACT FROM AUTHOR]
- Subjects :
- HUMAN behavior
REINFORCEMENT learning
UTILITY functions
PUBLIC goods
Subjects
Details
- Language :
- English
- ISSN :
- 13873954
- Volume :
- 28
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Mathematical & Computer Modelling of Dynamical Systems
- Publication Type :
- Academic Journal
- Accession number :
- 161131037
- Full Text :
- https://doi.org/10.1080/13873954.2022.2039717