The study examined how different communication regimes affect a swarm of 200 trading agents from four model families over seven U.S. trading days. Groups that could communicate—via isolation, message boards, or shared notes—tended to hold more of the same stocks than isolated groups, and agents were more likely to reuse phrases seen in group posts. While seeing a groupmate’s post increased phrase reuse, it did not noticeably alter that morning’s trades, though communicating groups tended to sell in step more often than isolated ones.
By Avid Fayaz, Harry Zhang, H{\aa}vard Alstadheim, Erik Nordl\"of, Vilhelm Karlin, Andr\'e Silva
arXiv:2606. 03544v1 Announce Type: new Abstract: Self-improving language agents are typically evaluated in isolation: an agent attempts a task, receives feedback, and iteratively refines its own behavior.
By Linyue Pan, Yaoming Zhu, Lin Qiu, Xuezhi Cao, Xunliang Cai
arXiv:2610.20360v1 Announce Type: new
Abstract: Gossip, defined as evaluative talk about absent third parties, is widely seen as a uniquely human social practice. This study examines whether comparab...
By Yong-Hui Hua, Chih-Han Lin, Shu-Kai Hsieh
The Flag Game is a toy model designed to study how AI agents form collective beliefs. In the game, each agent sees only a private crop of a hidden country flag and can share beliefs with peers, leading to complex phenomena such as non‑monotonic performance scaling, accuracy gains from social awareness, and polarization that degrades performance at large population sizes. The authors introduce social circuit attribution to identify key agents and views, and develop a statistical mechanical theory to explain collective belief collapse and polarization in larger populations.
By Elizabeth Pavlova, Hidenori Tanaka
arXiv:2610.24833v1 Announce Type: cross
Abstract: As AI agents become increasingly connected through networks and take on tasks that require negotiation and joint decision-making, a systematic approa...
By Jin Gao
arXiv:2608. 16801v1 Announce Type: new Abstract: We study how teams of AI coding agents coordinate while solving programming tasks.
By Giuseppe Destefanis, Tomaso Aste