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20162026
most citedStarCraft II: A New Challenge for Reinforcement Learning

682 citations · 1.1k across the 20 of their papers we have counts for

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Showing 2026Show all

6 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

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.NE2026

A Theory of Appropriateness That Accounts for Norms of Rationality

Joel Z. Leibo, Alexander Sasha Vezhnevets, Manfred Diaz +10

We propose a society-first theory of normative appropriateness where individuals, modeled as pre-trained actors with cognitive architectures analogous to Large Language Models (LLM…

cs.MA2026

A Generative Model of Conspicuous Consumption and Status Signaling

Logan Cross, Jordi Grau-Moya, William A. Cunningham +2

Status signaling drives human behavior and the allocation of scarce resources such as mating opportunities, yet the generative mechanisms governing how specific goods, signals, or…

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…