8.9k citations · 11.5k across the 56 of their papers we have counts for
13 papers · 1 filter
MaD Physics: Evaluating information seeking under constraints in physical environments
Moksh Jain, Mehdi Bennani, Johannes Bausch +4
Scientific discovery is fundamentally a resource-constrained process that requires navigating complex trade-offs between the quality and quantity of measurements due to physical an…
Intelligent AI Delegation
Nenad Tomašev, Matija Franklin, Simon Osindero
AI agents are able to tackle increasingly complex tasks. To achieve more ambitious goals, AI agents need to be able to meaningfully decompose problems into manageable sub-component…
Distributional AGI Safety
Nenad Tomašev, Matija Franklin, Julian Jacobs +2
AI safety and alignment research has predominantly been focused on methods for safeguarding individual AI systems, resting on the assumption of an eventual emergence of a monolithi…
Virtual Agent Economies
Nenad Tomasev, Matija Franklin, Joel Z. Leibo +4
The rapid adoption of autonomous AI agents is giving rise to a new economic layer where agents transact and coordinate at scales and speeds beyond direct human oversight. We propos…
Multi-Actor Generative Artificial Intelligence as a Game Engine
Alexander Sasha Vezhnevets, Jayd Matyas, Logan Cross +6
Generative AI can be used in multi-actor environments with purposes ranging from social science modeling to interactive narrative and AI evaluation. Supporting this diversity of us…
Societal and technological progress as sewing an ever-growing, ever-changing, patchy, and polychrome quilt
Joel Z. Leibo, Alexander Sasha Vezhnevets, William A. Cunningham +3
Artificial Intelligence (AI) systems are increasingly placed in positions where their decisions have real consequences, e.g., moderating online spaces, conducting research, and adv…
A theory of appropriateness with applications to generative artificial intelligence
Joel Z. Leibo, Alexander Sasha Vezhnevets, Manfred Diaz +11
What is appropriateness? Humans navigate a multi-scale mosaic of interlocking notions of what is appropriate for different situations. We act one way with our friends, another with…
Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia
Alexander Sasha Vezhnevets, John P. Agapiou, Avia Aharon +7
Agent-based modeling has been around for decades, and applied widely across the social and natural sciences. The scope of this research method is now poised to grow dramatically as…
Solving MaxSAT with Matrix Multiplication
David Warde-Farley, Vinod Nair, Yujia Li +3
We propose an incomplete algorithm for Maximum Satisfiability (MaxSAT) specifically designed to run on neural network accelerators such as GPUs and TPUs. Given a MaxSAT problem ins…
Generative Art Using Neural Visual Grammars and Dual Encoders
Chrisantha Fernando, S. M. Ali Eslami, Jean-Baptiste Alayrac +3
Whilst there are perhaps only a few scientific methods, there seem to be almost as many artistic methods as there are artists. Artistic processes appear to inhabit the highest orde…
From Language Games to Drawing Games
Chrisantha Fernando, Daria Zenkova, Stanislav Nikolov +1
We attempt to automate various artistic processes by inventing a set of drawing games, analogous to the approach taken by emergent language research in inventing communication game…
FeUdal Networks for Hierarchical Reinforcement Learning
Alexander Sasha Vezhnevets, Simon Osindero, Tom Schaul +4
We introduce FeUdal Networks (FuNs): a novel architecture for hierarchical reinforcement learning. Our approach is inspired by the feudal reinforcement learning proposal of Dayan a…
Strategic Attentive Writer for Learning Macro-Actions
Alexander, Vezhnevets, Volodymyr Mnih +5
We present a novel deep recurrent neural network architecture that learns to build implicit plans in an end-to-end manner by purely interacting with an environment in reinforcement…