1.2k citations · 4.4k across the 42 of their papers we have counts for
8 papers · 1 filter
Biases for Emergent Communication in Multi-agent Reinforcement Learning
Tom Eccles, Yoram Bachrach, Guy Lever +2
We study the problem of emergent communication, in which language arises because speakers and listeners must communicate information in order to solve tasks. In temporally extended…
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert +9
Constructing agents with planning capabilities has long been one of the main challenges in the pursuit of artificial intelligence. Tree-based planning methods have enjoyed huge suc…
A Generalized Training Approach for Multiagent Learning
Paul Muller, Shayegan Omidshafiei, Mark Rowland +12
This paper investigates a population-based training regime based on game-theoretic principles called Policy-Spaced Response Oracles (PSRO). PSRO is general in the sense that it (1)…
Learning Truthful, Efficient, and Welfare Maximizing Auction Rules
Andrea Tacchetti, DJ Strouse, Marta Garnelo +2
From social networks to supply chains, more and more aspects of how humans, firms and organizations interact is mediated by artificial learning agents. As the influence of machine…
Differentiable Game Mechanics
Alistair Letcher, David Balduzzi, Sebastien Racaniere +4
Deep learning is built on the foundational guarantee that gradient descent on an objective function converges to local minima. Unfortunately, this guarantee fails in settings, such…
Autocurricula and the Emergence of Innovation from Social Interaction: A Manifesto for Multi-Agent Intelligence Research
Joel Z. Leibo, Edward Hughes, Marc Lanctot +1
Evolution has produced a multi-scale mosaic of interacting adaptive units. Innovations arise when perturbations push parts of the system away from stable equilibria into new regime…