4 citations · 4 across the 1 of their papers we have counts for
2 papers
cs.GT2024
Safe Pareto Improvements for Expected Utility Maximizers in Program Games
Anthony DiGiovanni, Jesse Clifton, Nicolas Macé
Agents in mixed-motive coordination problems such as Chicken may fail to coordinate on a Pareto-efficient outcome. Safe Pareto improvements (SPIs) were originally proposed to mitig…
cs.GT2021★ 4 cited
Survey of Self-Play in Reinforcement Learning
Anthony DiGiovanni, Ethan C. Zell
In reinforcement learning (RL), the term self-play describes a kind of multi-agent learning (MAL) that deploys an algorithm against copies of itself to test compatibility in variou…