The evaluation of generative agents’ behavior in this study was
limited to a relatively short timescale, and future research should
aim to observe their behavior over an extended period to gain a
more comprehensive understanding of their capabilities and lim-
itations. Varying and contrasting the underlying models, as well
as the hyperparameters used for the agents during future simu-
lations, could provide valuable insights into the impact of these
factors on the agents’ behavior. Additionally, given the known bi-
ases of language models, it is possible that generative agents may
output behavior or stereotypes that reflect bias. To mitigate this,
further work on value alignment will be necessary. Furthermore,
as with many large language models, generative agents may fail
to generate believable behavior for some subpopulations, particu-
larly marginalized populations, due to data deserts. We also have
limited knowledge of the robustness of generative agents. They
Generative Agents- Interactive Simulacra of Human Behavior