75 citations · 221 across the 11 of their papers we have counts for
4 papers · 1 filter
Emergent Bartering Behaviour in Multi-Agent Reinforcement Learning
Michael Bradley Johanson, Edward Hughes, Finbarr Timbers +1
Advances in artificial intelligence often stem from the development of new environments that abstract real-world situations into a form where research can be done conveniently. Thi…
Open Problems in Cooperative AI
Allan Dafoe, Edward Hughes, Yoram Bachrach +5
Problems of cooperation--in which agents seek ways to jointly improve their welfare--are ubiquitous and important. They can be found at scales ranging from our daily routines--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…
Learning to Understand Goal Specifications by Modelling Reward
Dzmitry Bahdanau, Felix Hill, Jan Leike +4
Recent work has shown that deep reinforcement-learning agents can learn to follow language-like instructions from infrequent environment rewards. However, this places on environmen…