May the best man win: Simulation optimization for match-making in e-sports

Ilya O. Ryzhov, Awais Tariq, Warren B. Powell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations


We consider the problem of automated match-making in a competitive online gaming service. Large numbers of players log on to the service and indicate their availability. The system must then find an opponent for each player, with the objective of creating competitive, challenging games that do not heavily favour either side, for as many players as possible. Existing mathematical models for this problem assume that each player has a skill level that is unknown to the game master. As more games are played, the game master's belief about player skills evolves according to a Bayesian learning model, allowing the game master to adaptively improve the quality of future games as information is being collected. We propose a new decision-making policy in this setting, based on the knowledge gradient concept from the literature on optimal learning. We conduct simulations to demonstrate the potential of this policy.

Original languageEnglish (US)
Title of host publicationProceedings of the 2011 Winter Simulation Conference, WSC 2011
Number of pages12
StatePublished - 2011
Event2011 Winter Simulation Conference, WSC 2011 - Phoenix, AZ, United States
Duration: Dec 11 2011Dec 14 2011

Publication series

NameProceedings - Winter Simulation Conference
ISSN (Print)0891-7736


Other2011 Winter Simulation Conference, WSC 2011
Country/TerritoryUnited States
CityPhoenix, AZ

All Science Journal Classification (ASJC) codes

  • Software
  • Modeling and Simulation
  • Computer Science Applications


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