Recent advances in agentic Artificial Intelligence (AI) systems have marked a shift in AI for Science: moving away from the use of individual AI systems for narrow task execution, toward multi-agent systems capable of orchestrating complex, end-to-end research workflows and performing (semi-)autonomous scientific disco...
Nenad Tomasev, Matija Franklin, Atoosa Kasirzadeh et al.· 0 citations
This technical report details the infrastructure behind Game Arena and describes the three pilot game environments: Chess, Poker, and Werewolf, enabling a systematic study of models's strategic planning, adaptation, and robustness under uncertainty.
Bovard Doerschuk-Tiberi, Yao Yan, Justin Chiu et al.· 0 citations
This work introduces a flexible and extensible mathematical modelling framework, rooted in social physics, aimed at answering macro-level questions regarding the evolving social norms in human populations under the assumption of frequent AI use, and advocates for the wider adoption of these kinds of social physics mode...
Nenad Tomasev, Matija Franklin, Simon Osindero· arXiv.org· 1 citation
Multi-agent AI science ecosystems rely on agents possessing tools that allow them to communicate, coordinate, and build on each other's work. Yet this shared infrastructure can also introduce vulnerabilities by creating a substrate for the contagious spread of unintended and undesirable behaviors. We report a case stud...
Davide Paglieri, Logan Cross, Tim Genewein et al.· 3 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
