71 citations · 153 across the 6 of their papers we have counts for
6 papers
Modeling human reputation-seeking behavior in a spatio-temporally complex public good provision game
Edward Hughes, Tina O. Zhu, Martin J. Chadwick +6
Multi-agent reinforcement learning algorithms are useful for simulating social behavior in settings that are too complex for other theoretical approaches like game theory. However,…
Human-centered mechanism design with Democratic AI
Raphael Koster, Jan Balaguer, Andrea Tacchetti +8
Building artificial intelligence (AI) that aligns with human values is an unsolved problem. Here, we developed a human-in-the-loop research pipeline called Democratic AI, in which…
A multi-agent reinforcement learning model of reputation and cooperation in human groups
Kevin R. McKee, Edward Hughes, Tina O. Zhu +7
Collective action demands that individuals efficiently coordinate how much, where, and when to cooperate. Laboratory experiments have extensively explored the first part of this pr…
Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agents
Jane X. Wang, Michael King, Nicolas Porcel +14
There has been rapidly growing interest in meta-learning as a method for increasing the flexibility and sample efficiency of reinforcement learning. One problem in this area of res…
Relational inductive bias for physical construction in humans and machines
Jessica B. Hamrick, Kelsey R. Allen, Victor Bapst +4
While current deep learning systems excel at tasks such as object classification, language processing, and gameplay, few can construct or modify a complex system such as a tower of…
Inequity aversion improves cooperation in intertemporal social dilemmas
Edward Hughes, Joel Z. Leibo, Matthew G. Phillips +9
Groups of humans are often able to find ways to cooperate with one another in complex, temporally extended social dilemmas. Models based on behavioral economics are only able to ex…