4 papers
Humans Are More Diverse: Frontier LLMs Show Extreme Policies in Idealised AI Development Races
Phu Hoa Pham, Duy Minh Dao Sy, Trung Kiet Huynh +9
An AI development race creates a multi-agent safety dilemma. Each company can develop slowly and safely, or move faster while taking a risk that may remove its final reward. We use…
Payoff scaling shapes cooperation in LLM agents across languages
Trung-Kiet Huynh, Dao-Sy Duy-Minh, Thanh-Bang Cao +13
Large language models (LLMs) are increasingly deployed as autonomous agents that negotiate, coordinate, and act on behalf of users. Whether they cooperate in such settings is no lo…
Understanding LLM Agent Behaviours via Game Theory: Strategy Recognition, Biases and Multi-Agent Dynamics
Trung-Kiet Huynh, Duy-Minh Dao-Sy, Thanh-Bang Cao +13
As Large Language Models (LLMs) increasingly operate as autonomous decision-makers in interactive and multi-agent systems and human societies, understanding their strategic behavio…
On the Optimality of Discrete Object Naming: a Kinship Case Study
Phong Le, Mees Lindeman, Raquel G. Alhama
The structure of naming systems in natural languages hinges on a trade-off between high informativeness and low complexity. Prior work capitalizes on information theory to formaliz…