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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 32

AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games

March 15, 2023

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Published Date: 2018-02-08

Registration: ISSN 2374-3468 (Online) ISSN 2159-5399 (Print)

Copyright: Published by AAAI Press, Palo Alto, California USA Copyright © 2018, Association for the Advancement of Artificial Intelligence All Rights Reserved.

Authors

Neil Burch

University of Alberta


Martin Schmid

Charles University in Prague


Matej Moravcik

Charles University in Prague


Dustin Morill

University of Alberta


Michael Bowling

University of Alberta


DOI:

10.1609/aaai.v32i1.11481


Abstract:

Evaluating agent performance when outcomes are stochastic and agents use randomized strategies can be challenging when there is limited data available. The variance of sampled outcomes may make the simple approach of Monte Carlo sampling inadequate. This is the case for agents playing heads-up no-limit Texas hold'em poker, whereman-machine competitions typically involve multiple days of consistent play by multiple players, but still can (and sometimes did) result in statistically insignificant conclusions. In this paper, we introduce AIVAT, a low variance, provably unbiased value assessment tool that exploits an arbitrary heuristic estimate of state value, as well as the explicit strategy of a subset of the agents. Unlike existing techniques which reduce the variance from chance events, or only consider game ending actions, AIVAT reduces the variance both from choices by nature and by players with a known strategy. The resulting estimator produces results that significantly outperform previous state of the art techniques. It was able to reduce the standard deviation of a Texas hold'em poker man-machine match by 85% and consequently requires 44 times fewer games to draw the same statistical conclusion. AIVAT enabled the first statistically significant AI victory against professional poker players in no-limit hold'em.Furthermore, the technique was powerful enough to produce statistically significant results versus individual players, not just an aggregate pool of the players. We also used AIVAT to analyze a short series of AI vs human poker tournaments,producing statistical significant results with as few as 28 matches.

Topics: AAAI

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HOW TO CITE:

Neil Burch||Martin Schmid||Matej Moravcik||Dustin Morill||Michael Bowling AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games Proceedings of the AAAI Conference on Artificial Intelligence, 32 (2018) .

Neil Burch||Martin Schmid||Matej Moravcik||Dustin Morill||Michael Bowling AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games AAAI 2018, .

Neil Burch||Martin Schmid||Matej Moravcik||Dustin Morill||Michael Bowling (2018). AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games. Proceedings of the AAAI Conference on Artificial Intelligence, 32, .

Neil Burch||Martin Schmid||Matej Moravcik||Dustin Morill||Michael Bowling. AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games. Proceedings of the AAAI Conference on Artificial Intelligence, 32 2018 p..

Neil Burch||Martin Schmid||Matej Moravcik||Dustin Morill||Michael Bowling. 2018. AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games. "Proceedings of the AAAI Conference on Artificial Intelligence, 32". .

Neil Burch||Martin Schmid||Matej Moravcik||Dustin Morill||Michael Bowling. (2018) "AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games", Proceedings of the AAAI Conference on Artificial Intelligence, 32, p.

Neil Burch||Martin Schmid||Matej Moravcik||Dustin Morill||Michael Bowling, "AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games", AAAI, p., 2018.

Neil Burch||Martin Schmid||Matej Moravcik||Dustin Morill||Michael Bowling. "AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games". Proceedings of the AAAI Conference on Artificial Intelligence, 32, 2018, p..

Neil Burch||Martin Schmid||Matej Moravcik||Dustin Morill||Michael Bowling. "AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games". Proceedings of the AAAI Conference on Artificial Intelligence, 32, (2018): .

Neil Burch||Martin Schmid||Matej Moravcik||Dustin Morill||Michael Bowling. AIVAT: A New Variance Reduction Technique for Agent Evaluation in Imperfect Information Games. AAAI[Internet]. 2018[cited 2023]; .


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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