343 citations · 591 across the 4 of their papers we have counts for
3 papers · 1 filter
Solving Common-Payoff Games with Approximate Policy Iteration
Samuel Sokota, Edward Lockhart, Finbarr Timbers +6
For artificially intelligent learning systems to have widespread applicability in real-world settings, it is important that they be able to operate decentrally. Unfortunately, dece…
Human-Agent Cooperation in Bridge Bidding
Edward Lockhart, Neil Burch, Nolan Bard +4
We introduce a human-compatible reinforcement-learning approach to a cooperative game, making use of a third-party hand-coded human-compatible bot to generate initial training data…
Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent
Edward Lockhart, Marc Lanctot, Julien Pérolat +4
In this paper, we present exploitability descent, a new algorithm to compute approximate equilibria in two-player zero-sum extensive-form games with imperfect information, by direc…