3 citations · 9 across the 19 of their papers we have counts for
5 papers · 1 filter
Observe, Share, or Predict? Disentangling Partner Information in Embodied Multi-Agent Collaboration
Adrián Szlatincsán, Filippo Ziliotto, Bruno Lepri +3
LLMs are used as high-level controllers for embodied agents, but it remains unclear whether they support collaborative reasoning, such as anticipating a collaborator's actions in r…
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…
Mirror, Mirror on the Wall: Can VLM Agents Tell Who They Are at All?
Filippo Ziliotto, Ciro Beneduce, Bruno Lepri +3
In the animal kingdom, mirror self-recognition is a canonical probe of higher-order cognition, emerging only in some species. We ask whether an analogous functional capability emer…
LLMberjack: Guided Trimming of Debate Trees for Multi-Party Conversation Creation
Leonardo Bottona, Nicolò Penzo, Bruno Lepri +2
We present LLMberjack, a platform for creating multi-party conversations starting from existing debates, originally structured as reply trees. The system offers an interactive inte…