@L_Ferrarotti
Joined September 2023
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📢 New pre-print out! Our point of view on the study of generative AI collective behavior 🤖
Gian Maria Campedelli@CampedelliGianFeb 2
Given the lively debate on #moltbook, let me signal this pre-print we recently released on the need for an interactionist paradigm for studying multi-agent AI systems. We discuss 4 directions we consider crucial for studying LLM-based collectives. arxiv.org/abs/2601.10567

Generative AI collective behavior needs an interactionist paradigm

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 terms of risks...

arxiv.org
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📡⚠️I have a new pre-print out! In "A Criminology of Machines" I discuss why it is relevant that criminologists start engaging with the risks associated with potential emergent behaviors of multi-agent AI systems: arxiv.org/abs/2511.02895 1/7

A Criminology of Machines

While the possibility of reaching human-like Artificial Intelligence (AI) remains controversial, the likelihood that the future will be characterized by a society with a growing presence of...

arxiv.org
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📢 The preprint of our work on human cooperation prediction is out! 🎉 arxiv.org/abs/2412.16121

Predicting human cooperation: sensitizing drift-diffusion model to...

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 identify which...

arxiv.org
Lucila Álvarez-Žužek@lualvarezzuzek23 Dec 2024
📣 New preprint out 🚨 "Predicting human cooperation: sensitizing drift-diffusion model to interaction and external stimuli" 👥 Co-authored with @L_Ferrarotti and in collab with @brulepri and @ricgallotti Check it out on arXiv : arxiv.org/abs/2412.16121

Predicting human cooperation: sensitizing drift-diffusion model to...

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 identify which...

arxiv.org
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Our work has been accepted at #AAAI25! So thrilled! 🥳🥳🥳 Check it out in this post or on arxiv!
Mátyás Vincze@vinczematyas_18 Dec 2024
🎉 Our work "SMOSE: Sparse Mixture of Shallow Experts for Interpretable Reinforcement Learning in Continuous Control Tasks" has been accepted by AAAI 2025! #AAAI2025 paper: arxiv.org/abs/2412.13053 with @L_Ferrarotti, @brulepri, @gih82 🧵1/6
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We won 😍 so happy about this!
Leonardo Lucio Custode@LLCustode17 Jul 2024
Happy to share that we won the Interpretable Control Competition @ #GECCO24 ! Congrats @vinczematyas_ @L_Ferrarotti @gih82 @brulepri
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🤖🤓 Great experience at Ma+Be24! machinebehavior.science/ I was happy to chat about our last results on "Modeling the effect of interaction on human decisions: a step towards AI for Cooperation" @lualvarezzuzek @ricgallotti @brulepri – at Berlin, Germany
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🤖Welcome to the forefront of behavioral science in the digital age! The conference on Machine+Behavior, hosted by @Max_Planck_CHM, just started 👏 – join online! 👀👂youtube.com/watch?v=kz_cdk6J… For more information, visit: machinebehavior.science/
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Laura Ferrarotti retweeted
MobS Group @ FBK@MobS_FBK16 Apr 2024
🚨Welcome at the Mobile and Social Computing Research Group @FBK_research official account! 💻In the next weeks we are going to give some insights about our group members... Stay tuned👀
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