4 papers
KERAIA: An Adaptive and Explainable Framework for Dynamic Knowledge Representation and Reasoning
Stephen Richard Varey, Alessandro Di Stefano, The Anh Han
In this paper, we introduce KERAIA, a novel framework and software platform for symbolic knowledge engineering designed to address the persistent challenges of representing, reason…
Do LLMs trust AI regulation? Emerging behaviour of game-theoretic LLM agents
Alessio Buscemi, Daniele Proverbio, Paolo Bova +15
There is general agreement that fostering trust and cooperation within the AI development ecosystem is essential to promote the adoption of trustworthy AI systems. By embedding Lar…
FAIRGAME: a Framework for AI Agents Bias Recognition using Game Theory
Alessio Buscemi, Daniele Proverbio, Alessandro Di Stefano +3
Letting AI agents interact in multi-agent applications adds a layer of complexity to the interpretability and prediction of AI outcomes, with profound implications for their trustw…
Quantifying detection rates for dangerous capabilities: a theoretical model of dangerous capability evaluations
Paolo Bova, Alessandro Di Stefano, The Anh Han
We present a quantitative model for tracking dangerous AI capabilities over time. Our goal is to help the policy and research community visualise how dangerous capability testing c…