Games Agents Play: Towards Transactional Analysis in LLM-based Multi-Agent Systems

Fuente: arXiv
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Autores principales: Zamojska, Monika, Chudziak, Jarosław A.
Formato: Preprint
Publicado: 2025
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author Zamojska, Monika
Chudziak, Jarosław A.
author_facet Zamojska, Monika
Chudziak, Jarosław A.
contents Multi-Agent Systems (MAS) are increasingly used to simulate social interactions, but most of the frameworks miss the underlying cognitive complexity of human behavior. In this paper, we introduce Trans-ACT (Transactional Analysis Cognitive Toolkit), an approach embedding Transactional Analysis (TA) principles into MAS to generate agents with realistic psychological dynamics. Trans-ACT integrates the Parent, Adult, and Child ego states into an agent's cognitive architecture. Each ego state retrieves context-specific memories and uses them to shape response to new situations. The final answer is chosen according to the underlying life script of the agent. Our experimental simulation, which reproduces the Stupid game scenario, demonstrates that agents grounded in cognitive and TA principles produce deeper and context-aware interactions. Looking ahead, our research opens a new way for a variety of applications, including conflict resolution, educational support, and advanced social psychology studies.
format Preprint
id arxiv_https___arxiv_org_abs_2507_21354
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Games Agents Play: Towards Transactional Analysis in LLM-based Multi-Agent Systems
Zamojska, Monika
Chudziak, Jarosław A.
Artificial Intelligence
Multiagent Systems
Multi-Agent Systems (MAS) are increasingly used to simulate social interactions, but most of the frameworks miss the underlying cognitive complexity of human behavior. In this paper, we introduce Trans-ACT (Transactional Analysis Cognitive Toolkit), an approach embedding Transactional Analysis (TA) principles into MAS to generate agents with realistic psychological dynamics. Trans-ACT integrates the Parent, Adult, and Child ego states into an agent's cognitive architecture. Each ego state retrieves context-specific memories and uses them to shape response to new situations. The final answer is chosen according to the underlying life script of the agent. Our experimental simulation, which reproduces the Stupid game scenario, demonstrates that agents grounded in cognitive and TA principles produce deeper and context-aware interactions. Looking ahead, our research opens a new way for a variety of applications, including conflict resolution, educational support, and advanced social psychology studies.
title Games Agents Play: Towards Transactional Analysis in LLM-based Multi-Agent Systems
topic Artificial Intelligence
Multiagent Systems
url https://arxiv.org/abs/2507.21354