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20202026
most citedBoth eyes open: Vigilant Incentives help Regulatory Markets improve AI Safety

4 citations · 9 across the 18 of their papers we have counts for

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11 papers · 1 filter

cs.GT2026

Cooperation Without Adaptation: LLM Agents in a Collective-Risk Dilemma

Trung-Kiet Huynh, Dao-Sy Duy-Minh, Chi-Nguyen Tran +4

Language-model agents are increasingly deployed to act on behalf of people in settings where individual decisions shape shared outcomes. We examine whether five production models a…

cs.GT2026

Network Topology Shapes AI Intervention Effectiveness on Deception: Truth-Telling vs. Investigative Agents

Zhao Song, Stefan Sarkadi, The Anh Han

Deploying AI agents to combat dishonest communication is an intuitive response to deception in hybrid human-AI societies. However, the efficacy of such interventions in realistic n…

cs.AI2026

When Numbers Start Talking: Numerical Signalling and Strategic Behaviour Among LLMs

Alessio Buscemi, Daniele Proverbio, Alessandro Di Stefano +3

Large language model (LLM)-based agents increasingly operate in multi-agent systems (MAS) characterised by strategic interaction. However, little is known about whether, and to wha…

cs.AI2026

Reputation-driven Cooperation in Lattice-based Decentralized Federated Learning through Evolutionary Game Theory

Phuc Hoang Truong Huynh, Dung Tran Vinh, Khoa Duc Anh Lam +9

Decentralized Federated Learning (DFL) has emerged as an optimal privacy-preserving solution; however, it remains vulnerable to opportunistic behaviors due to the absence of a cent…

cs.AI2026

Humans Are More Diverse: Frontier LLMs Show Extreme Policies in Idealised AI Development Races

Phu Hoa Pham, Duy Minh Dao Sy, Trung Kiet Huynh +9

An AI development race creates a multi-agent safety dilemma. Each company can develop slowly and safely, or move faster while taking a risk that may remove its final reward. We use…

cs.AI2026

Co-evolution of social reward and punishment under institutional interventions

Van An Nguyen, Vuong Khang Huynh, Hoai Thuong Nguyen +14

We investigate how peer and institutional incentives jointly shape the evolution of cooperation, social welfare, and enforcement efficiency in social dilemmas. In a Prisoners Dilem…

cs.AI2026

Falling Behind Drives Unsafe Development in an Idealised AI Race Experiment

Elias Fernández Domingos, The Anh Han

Technological races create tension between speed and safety: actors may gain by moving faster than competitors, even when risky development is harmful. This is prominent in debates…

cs.GT2026

Network Reciprocity Shapes Evolutionary Cybersecurity Dynamics

Adeela Bashir, Zia Ush Shamszaman, Zhao Song +1

AI-assisted cybersecurity systems are characterised by continuous adaptation between attackers and defenders, making evolutionary game theory a natural framework for studying their…

cs.CY2026

Prioritization of Risks from Artificial Intelligence: A Delphi Study of 272 International Experts

Alexander K. Saeri, Jess Graham, Michael Noetel +185

Artificial intelligence poses many risks, ranging from familiar present-day harms to unprecedented and potentially catastrophic ones. Effective risk management requires prioritizat…

cs.AI2026

Trust or Check? Understanding the (Evolutionary) Dynamics of User Trust in AI Systems

Adeela Bashir, Zhao Song, Ndidi Bianca Ogbo +21

As the capabilities and adoption of Artificial Intelligence (AI) systems grow, trust in these AI systems is an increasingly urgent concern. Much research has focused on models of A…

cs.AI2026

Payoff scaling shapes cooperation in LLM agents across languages

Trung-Kiet Huynh, Dao-Sy Duy-Minh, Thanh-Bang Cao +13

Large language models (LLMs) are increasingly deployed as autonomous agents that negotiate, coordinate, and act on behalf of users. Whether they cooperate in such settings is no lo…