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20162026
most citedMulti-agent Reinforcement Learning in Sequential Social Dilemmas

277 citations · 754 across the 54 of their papers we have counts for

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29 papers · 1 filter

cs.AI2026

A Case Study on Emergent Cheating and Whistleblowing in Autonomous Research Swarms

Davide Paglieri, Logan Cross, Tim Genewein +3

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 als…

cs.AI2026

Solipsistic Superintelligence is Unlikely to be Cooperative

Rakshit S Trivedi, Natasha Jaques, Logan Cross +2

AI's central challenge is shifting from capability to coexistence. The dominant paradigm in AI research focuses on developing powerful agents that treat the world as an exogenous a…

cs.AI2026

From AGI to ASI

Tim Genewein, Matija Franklin, Alexander Lerchner +11

Over the last decade, building human-level artificial general intelligence has moved from far-fetched speculation to being a concrete next-decade target for many of the largest AI…

cs.AI2026

Stabilising Generative Models of Attitude Change

Jayd Matyas, William A. Cunningham, Alexander Sasha Vezhnevets +3

Attitude change - the process by which individuals revise their evaluative stances - has been explained by a set of influential but competing verbal theories. These accounts often…

cs.AI2026

Persona Generators: Generating Diverse Synthetic Personas for Arbitrary Contexts

Davide Paglieri, Logan Cross, William A. Cunningham +2

Evaluating AI systems that interact with humans requires understanding their behavior across diverse user populations, but collecting representative human data is often expensive o…

cs.AI2026★ 1 cited

Generative AI collective behavior needs an interactionist paradigm

Laura Ferrarotti, Gian Maria Campedelli, Roberto Dessì +7

In this article, we argue that understanding the collective behavior of agents based on large language models (LLMs) is an essential area of inquiry, with important implications in…