147 citations · 177 across the 13 of their papers we have counts for
13 papers
Proportionally Fair Matching via Randomized Rounding
Sharmila Duppala, Nathaniel Grammel, Juan Luque +2
Given an edge-colored graph, the goal of the proportional fair matching problem is to find a maximum weight matching while ensuring proportional representation (with respect to the…
On (Random-order) Online Contention Resolution Schemes for the Matching Polytope of (Bipartite) Graphs
Calum MacRury, Will Ma, Nathaniel Grammel
Online Contention Resolution Schemes (OCRS's) represent a modern tool for selecting a subset of elements, subject to resource constraints, when the elements are presented to the al…
The Stochastic Boolean Function Evaluation Problem for Symmetric Boolean Functions
Dimitrios Gkenosis, Nathaniel Grammel, Lisa Hellerstein +1
We give two approximation algorithms solving the Stochastic Boolean Function Evaluation (SBFE) problem for symmetric Boolean functions. The first is an -approximation al…
Improved Guarantees for Offline Stochastic Matching via New Ordered Contention Resolution Schemes
Brian Brubach, Nathaniel Grammel, Will Ma +2
Matching is one of the most fundamental and broadly applicable problems across many domains. In these diverse real-world applications, there is often a degree of uncertainty in the…
PettingZoo: Gym for Multi-Agent Reinforcement Learning
J. K. Terry, Benjamin Black, Nathaniel Grammel +10
This paper introduces the PettingZoo library and the accompanying Agent Environment Cycle ("AEC") games model. PettingZoo is a library of diverse sets of multi-agent environments w…
Agent Environment Cycle Games
J K Terry, Nathaniel Grammel, Benjamin Black +3
Partially Observable Stochastic Games (POSGs) are the most general and common model of games used in Multi-Agent Reinforcement Learning (MARL). We argue that the POSG model is conc…