We introduce the use of generative adversarial learning to compute equil...
Solution concepts such as Nash Equilibria, Correlated Equilibria, and Co...
The Game Theory Multi-Agent team at DeepMind studies several aspects...
From social networks to traffic routing, artificial learning agents are
...
Artificial learning agents are mediating a larger and larger number of
i...
Building artificial intelligence (AI) that aligns with human values is a...
Nash equilibrium is a central concept in game theory. Several Nash solve...
Even in simple multi-agent systems, fixed incentives can lead to outcome...
Recent advances in deep reinforcement learning (RL) have led to consider...
One of the fundamental challenges of governance is deciding when and how...
Auctions are protocols to allocate goods to buyers who have preferences ...
The behavioral dynamics of multi-agent systems have a rich and orderly
s...
Artificial intelligence (AI) has undergone a renaissance recently, makin...
From just a glance, humans can make rich predictions about the future st...
The complexity of a learning task is increased by transformations in the...
The present phase of Machine Learning is characterized by supervised lea...
We present GURLS, a least squares, modular, easy-to-extend software libr...