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Spotlight
Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games
Dustin Morrill · Ryan D'Orazio · Marc Lanctot · James Wright · Michael Bowling · Amy Greenwald

Wed Jul 21 07:35 AM -- 07:40 AM (PDT) @
in Learning Theory 5 »

Hindsight rationality is an approach to playing general-sum games that prescribes no-regret learning dynamics for individual agents with respect to a set of deviations, and further describes jointly rational behavior among multiple agents with mediated equilibria. To develop hindsight rational learning in sequential decision-making settings, we formalize behavioral deviations as a general class of deviations that respect the structure of extensive-form games. Integrating the idea of time selection into counterfactual regret minimization (CFR), we introduce the extensive-form regret minimization (EFR) algorithm that achieves hindsight rationality for any given set of behavioral deviations with computation that scales closely with the complexity of the set. We identify behavioral deviation subsets, the partial sequence deviation types, that subsume previously studied types and lead to efficient EFR instances in games with moderate lengths. In addition, we present a thorough empirical analysis of EFR instantiated with different deviation types in benchmark games, where we find that stronger types typically induce better performance.

Keywords: Game Theory and Computational Economics

Author Information

Dustin Morrill (University of Alberta; Alberta Machine Intelligence Institute)

I'm a Ph.D. candidate at the [University of Alberta](https://www.ualberta.ca/) and the [Alberta Machine Intelligence Institute (Amii)](https://www.amii.ca/), co-supervised by [Professor Michael Bowling](https://webdocs.cs.ualberta.ca/~bowling/) and [Professor Amy Greenwald](http://cs.brown.edu/people/faculty/amy/) of [Brown University](https://www.brown.edu/). I work on multi-agent learning and scaleable, dependable learning algorithms. I'm a coauthor of [DeepStack](https://www.deepstack.ai) and I created [Cepheus](http://poker.srv.ualberta.ca/)'s [public match interface](http://poker-play.srv.ualberta.ca/). I also manage the [Computer Poker Research Group (CPRG) website](http://poker.cs.ualberta.ca/). I completed a B.Sc. and M.Sc. in computing science at the University of Alberta where my M.Sc was supervised by Michael Bowling. As an undergraduate, I worked with the CPRG to create an [open-source web interface to play against poker bots](https://github.com/dmorrill10/acpc_poker_gui_client) and to develop the 1st-place 3-player Kuhn poker entry in the 2014 [Annual Computer Poker Competition (ACPC)](http://www.computerpokercompetition.org/).

Ryan D'Orazio (Université de Montréal)
Marc Lanctot (DeepMind)
James Wright (University of Alberta)
Michael Bowling (University of Alberta)
Amy Greenwald (Brown)

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