MOTIF: A Framework for Enhancing the Profiling Module of Generative Agents that Simulate Human Behavior

Tibério Cerqueira, Pamela Bezerra

2025

Abstract

Recent advances in Large Language Models (LLMs) have made the development of architectures that convincingly simulate human behavior possible. These architectures give rise to generative agents (GA), a new class of intelligent agents capable of carrying out human activities such as forming opinions, initiating dialogues, and planning the day. These experiences are stored as natural language and later transformed into reflections, which are then used to guide future actions. Some of the advantages of GA are the ability to operate in dynamic and open environments, interact with other agents in a more human-related way, and adapt to changes. These agents, however, require a complex development process. Given this, this study proposes MOTIF, a framework for facilitating and speeding up the initial stage of building these agents, known as profiling. This stage is responsible for defining the agents’ identities and personalities. However, profiling is very subjective and lacks a standard process, with some solutions manually writing each profile, while others use LLMs. MOTIF combines both manual and LLM-based methods to enable the development of agents with well-defined personalities and identities. Additionally, it provides a way of standardizing and formalizing the profiling stage, creating the basis for future research in this field.

Paper Citation

in Harvard Style

Cerqueira T. and Bezerra P. (2025). MOTIF: A Framework for Enhancing the Profiling Module of Generative Agents that Simulate Human Behavior. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 774-781. DOI: 10.5220/0013181800003890

in Bibtex Style

@conference{icaart25,
author={Tibério Cerqueira and Pamela Bezerra},
title={MOTIF: A Framework for Enhancing the Profiling Module of Generative Agents that Simulate Human Behavior},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2025},
pages={774-781},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013181800003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - MOTIF: A Framework for Enhancing the Profiling Module of Generative Agents that Simulate Human Behavior
SN - 978-989-758-737-5
AU - Cerqueira T.
AU - Bezerra P.
PY - 2025
SP - 774
EP - 781
DO - 10.5220/0013181800003890
PB - SciTePress