4 citations · 9 across the 18 of their papers we have counts for
9 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…
Enhancing Cancer Diagnosis with Explainable & Trustworthy Deep Learning Models
Badaru I. Olumuyiwa, The Anh Han, Zia U. Shamszaman
This research presents an innovative approach to cancer diagnosis and prediction using explainable Artificial Intelligence (XAI) and deep learning techniques. With cancer causing n…
Both eyes open: Vigilant Incentives help Regulatory Markets improve AI Safety
Paolo Bova, Alessandro Di Stefano, The Anh Han
In the context of rapid discoveries by leaders in AI, governments must consider how to design regulation that matches the increasing pace of new AI capabilities. Regulatory Markets…