Combining Incremental Strategy Generation and Branch and Bound Search for Computing Maxmin Strategies in Imperfect Recall Games

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00315397" target="_blank" >RIV/68407700:21230/17:00315397 - isvavai.cz</a>

Result on the web

<a href="https://www.researchgate.net/publication/317095657_Combining_incremental_strategy_generation_and_branch_and_bound_search_for_computing_maxmin_strategies_in_imperfect_recall_games" target="_blank" >https://www.researchgate.net/publication/317095657_Combining_incremental_strategy_generation_and_branch_and_bound_search_for_computing_maxmin_strategies_in_imperfect_recall_games</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Combining Incremental Strategy Generation and Branch and Bound Search for Computing Maxmin Strategies in Imperfect Recall Games

Original language description

Extensive-form games with imperfect recall are an important model of dynamic games where the players are allowed to forget previously known information. Often, imperfect recall games are the result of an abstraction algorithm that simplifies a large game with perfect recall. Unfortunately, solving an imperfect recall game has fundamental problems since a Nash equilibrium does not have to exist. Alternatively, we can seek maxmin strategies that guarantee an expected outcome. The only existing algorithm computing maxmin strategies in two-player imperfect recall games without absentmindedness, however, requires approximating a bilinear mathematical program that is proportional to the size of the whole game and thus has a limited scalability. We propose a novel algorithm for computing maxmin strategies in this class of games that combines this approximate algorithm with an incremental strategy-generation technique designed previously for extensive-form games with perfect recall. Experimental evaluation shows that the novel algorithm builds only a fraction of the game tree and improves the scalability by several orders of magnitude. Finally, we demonstrate that our algorithm can solve an abstracted variant of a large game faster compared to the algorithms operating on the unabstracted perfect-recall variant.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GA15-23235S" target="_blank" >GA15-23235S: Abstractions and Extensive-Form Games with Imperfect Recall</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 31th AAAI Conference on Artificial Intelligence

ISBN

978-1-57735-786-5

ISSN

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e-ISSN

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Number of pages

9

Pages from-to

902-910

Publisher name

AAAI Press

Place of publication

Menlo Park

Event location

San Francisco

Event date

Feb 4, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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