7 papers
Neural Parameter Calibration for Finite-State Mean Field Games
Anna C. M. Thöni, Grégoire Lambrecht, Gökçe Dayanıklı +3
Mean field games efficiently approximate a very large population of strategic agents. While these games can aid the understanding of complex systems, their deployment in real-world…
MINDGAMES: A Live Arena for Evaluating Social and Strategic Reasoning in Multi-Agent LLMs
Kevin Wang, Anna Thöni, Benjamin Kempinski +50
Large language models (LLMs) are increasingly deployed as interactive agents, yet their capacity for social and strategic reasoning over extended interaction remains poorly underst…
Neural Mean-Field Games: Extending Mean-Field Game Theory with Neural Stochastic Differential Equations
Anna C. M. Thöni, Yoram Bachrach, Tal Kachman
Mean-field game theory relies on approximating games that are intractable to model due to a very large to infinite population of players. While these kinds of games can be solved a…
David vs. Goliath: Verifiable Agent-to-Agent Jailbreaking via Reinforcement Learning
Samuel Nellessen, Tal Kachman
The evolution of large language models into autonomous agents introduces adversarial failures that exploit legitimate tool privileges, transforming safety evaluation in tool-augmen…
Evaluating Artificial Intelligence Algorithms for the Standardization of Transtibial Prosthetic Socket Shape Design
C. H. E. Jordaan, M. van der Stelt, T. J. J. Maal +4
The quality of a transtibial prosthetic socket depends on the prosthetist's skills and expertise, as the fitting is performed manually. This study investigates multiple artificial…
InfluenceNet: AI Models for Banzhaf and Shapley Value Prediction
Benjamin Kempinski, Tal Kachman
Power indices are essential in assessing the contribution and influence of individual agents in multi-agent systems, providing crucial insights into collaborative dynamics and deci…