Master thesis defense in Algolog section: Christian Juul Kisum
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Valentin Goranko
Jan 27, 2012, 9:12:53 AM1/27/12
to alg...@googlegroups.com, Peter Bro Miltersen, s04...@student.dtu.dk
Master thesis defense in Algolog. All are welcome.
Venue: build. 322, room 033.
Title: Implementation, test, and analysis of some solution concepts for repeated games and imperfect information games
Speaker: Christian Juul Kisum
Abstract: The work presented in this thesis studies some classical and new game-theoretic solution concepts for 2-player non-cooperative strategic form games. In particular, the thesis focuses on iterated regret minimization, proposed by Halpern and Pass in 2009, and its recently proposed variation, average regret minimization. These solution concepts, as well as Nash equilibrium, are implemented, experimented with and compared with each other on a variety of well-known games. The experiments showed, in particular, that average regret minimization has the same worst case time complexity as iterated regret minimization, but finds the results in a single iteration. Furthermore the results of average regret minimization compared closely to those of iterated regret minimization. This implied that average regret minimization appears a generally better solution than iterated regret minimization.
Time: Thursday, February 02, 11.30am
Venue: build. 322, room 033.
Title: Implementation, test, and analysis of some solution concepts for repeated games and imperfect information games
Speaker: Christian Juul Kisum
Abstract: The work presented in this thesis studies some classical and new game-theoretic solution concepts for 2-player non-cooperative strategic form games. In particular, the thesis focuses on iterated regret minimization, proposed by Halpern and Pass in 2009, and its recently proposed variation, average regret minimization. These solution concepts, as well as Nash equilibrium, are implemented, experimented with and compared with each other on a variety of well-known games. The experiments showed, in particular, that average regret minimization has the same worst case time complexity as iterated regret minimization, but finds the results in a single iteration. Furthermore the results of average regret minimization compared closely to those of iterated regret minimization. This implied that average regret minimization appears a generally better solution than iterated regret minimization.
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