233 citations · 581 across the 28 of their papers we have counts for
4 papers · 1 filter
Consequentialist conditional cooperation in social dilemmas with imperfect information
Alexander Peysakhovich, Adam Lerer
Social dilemmas, where mutual cooperation can lead to high payoffs but participants face incentives to cheat, are ubiquitous in multi-agent interaction. We wish to construct agents…
Prosocial learning agents solve generalized Stag Hunts better than selfish ones
Alexander Peysakhovich, Adam Lerer
Deep reinforcement learning has become an important paradigm for constructing agents that can enter complex multi-agent situations and improve their policies through experience. On…
Maintaining cooperation in complex social dilemmas using deep reinforcement learning
Adam Lerer, Alexander Peysakhovich
Social dilemmas are situations where individuals face a temptation to increase their payoffs at a cost to total welfare. Building artificially intelligent agents that achieve good…
Learning causal effects from many randomized experiments using regularized instrumental variables
Alexander Peysakhovich, Dean Eckles
Scientific and business practices are increasingly resulting in large collections of randomized experiments. Analyzed together, these collections can tell us things that individual…