April 30, 2018
Consequentialist Conditional Cooperation in Social Dilemmas with Imperfect Information
International Conference on Learning Representations (ICLR)
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 that cooperate with pure cooperators, avoid exploitation by pure defectors, and incentivize cooperation from the rest. We show how to construct such strategies using deep reinforcement learning techniques and demonstrate, both analytically and experimentally, that they are effective in social dilemmas beyond simple matrix games.
By: Alexander Peysakhovich, Adam Lerer