16 papers
Deal Me Maybe: The Role of Emotions in Multi-Agent Negotiation
Massimiliano Luca, Apoorva Singh, Bruno Lepri
Negotiation is a demanding social task for LLM agents, requiring strategic reasoning, persuasion, and interpersonal adaptation. Yet existing benchmarks often treat agents as emotio…
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…
AI's Blind Spots: Geographic Knowledge and Diversity Deficit in Generated Urban Scenario
Ciro Beneduce, Massimiliano Luca, Bruno Lepri
Diffusion-based text-to-image models are increasingly used for urban analysis and scenario generation, but their geographic knowledge and representational biases remain poorly unde…
pySpainMobility: Unlocking Spanish Open Mobility Data for Spatial Inequality Research
Ciro Beneduce, Tania Gullón Muñoz-Repiso, Bruno Lepri +1
Human mobility shapes access to resources, opportunities, and services, making movement data a powerful lens for studying spatial and social inequality. Yet despite the growing ava…
On Universality of Deep Equivariant Networks
Marco Pacini, Mircea Petrache, Bruno Lepri +2
Universality results for equivariant neural networks remain rare. Those that do exist typically hold only in restrictive settings: either they rely on regular or higher-order tenso…
Separation Power of Equivariant Neural Networks
Marco Pacini, Xiaowen Dong, Bruno Lepri +1
The separation power of a machine learning model refers to its ability to distinguish between different inputs and is often used as a proxy for its expressivity. Indeed, knowing th…