most citedGenerative AI collective behavior needs an interactionist paradigm

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

physics.soc-ph2026

Ant swarm functional control via stigmergic Reinforcement Learning agents

Alessio Pitteri, Andrea Guizzo, Laura Ferrarotti +2

In this work, we propose a novel framework for the functional controllability of the ant swarm model, a well-known and relevant model of collective behaviour. Our approach introduc…

cs.AI20261 cited

Generative AI collective behavior needs an interactionist paradigm

Laura Ferrarotti, Gian Maria Campedelli, Roberto Dessì +7

In this article, we argue that understanding the collective behavior of agents based on large language models (LLMs) is an essential area of inquiry, with important implications in…

physics.soc-ph2024

Predicting human cooperation: sensitizing drift-diffusion model to interaction and external stimuli

Lucila G. Alvarez-Zuzek, Laura Ferrarotti, Bruno Lepri +1

As humans perceive and actively engage with the world, we adjust our decisions in response to shifting group dynamics and are influenced by social interactions. This study aims to…

cs.LG2024

SMOSE: Sparse Mixture of Shallow Experts for Interpretable Reinforcement Learning in Continuous Control Tasks

Mátyás Vincze, Laura Ferrarotti, Leonardo Lucio Custode +2

Continuous control tasks often involve high-dimensional, dynamic, and non-linear environments. State-of-the-art performance in these tasks is achieved through complex closed-box po…

cs.AI2024

Autonomous and Human-Driven Vehicles Interacting in a Roundabout: A Quantitative and Qualitative Evaluation

Laura Ferrarotti, Massimiliano Luca, Gabriele Santin +9

Optimizing traffic dynamics in an evolving transportation landscape is crucial, particularly in scenarios where autonomous vehicles (AVs) with varying levels of autonomy coexist wi…