activity
20182026
most citedMulti-Agent Risks from Advanced AI

10 citations · 10 across the 3 of their papers we have counts for

collaborators

5 papers

cs.MA202510 cited

Multi-Agent Risks from Advanced AI

Lewis Hammond, Alan Chan, Jesse Clifton +41

The rapid development of advanced AI agents and the imminent deployment of many instances of these agents will give rise to multi-agent systems of unprecedented complexity. These s…

cs.AI2024

Possible Principles for Aligned Structure Learning Agents

Lancelot Da Costa, Tomáš Gavenčiak, David Hyland +5

This paper offers a roadmap for the development of scalable aligned artificial intelligence (AI) from first principle descriptions of natural intelligence. In brief, a possible pat…

cs.AI2020

Performance of Bounded-Rational Agents With the Ability to Self-Modify

Jakub Tětek, Marek Sklenka, Tomáš Gavenčiak

Self-modification of agents embedded in complex environments is hard to avoid, whether it happens via direct means (e.g. own code modification) or indirectly (e.g. influencing the…

stat.AP2020

How Robust are the Estimated Effects of Nonpharmaceutical Interventions against COVID-19?

Mrinank Sharma, Sören Mindermann, Jan Markus Brauner +7

To what extent are effectiveness estimates of nonpharmaceutical interventions (NPIs) against COVID-19 influenced by the assumptions our models make? To answer this question, we inv…

cs.DS2018

Compact I/O-Efficient Representation of Separable Graphs and Optimal Tree Layouts

Tomáš Gavenčiak, Jakub Tětek

Compact and I/O-efficient data representations play an important role in efficient algorithm design, as memory bandwidth and latency can present a significant performance bottlenec…