Selecting Robust Strategies Based on Abstracted
Game Models
Oscar Veliz and Christopher Kiekintveld
In IJCAI Workshop on Smart Simulation and Modelling for Complex Systems (SSMCS). 2015.
This is the author's version of the work.
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Abstract
Game theory is a tool for modeling multi-agent decision problems and
has been used to great success in modeling and simulating problems such as poker,
security, and trading agents. However, many real games are extremely large and
complex with multiple agent interactions. One approach for solving these games is
to use abstraction techniques to shrink the game to a form that can be solved by
removing detail and translating a solution back to the original. However, abstraction
introduces error into the model. We study ways to analyze games that are robust
to errors in the model of the game, including abstracted games. We empirically
evaluate several solution methods to examine how robust they are for abstracted
games.
