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We develop a point based method for solving finitely nested interactive POMDPs approximately. Analogously to point based value iteration (PBVI) in POMDPs, we maintain a set of belief points and form value functions composed of those value vectors that are optimal at these points. However, as we focus on multiagent settings, the beliefs are nested and computation of the value vectors relies on predicted actions of others. Consequently, we develop a novel interactive generalization of PBVI applicable to multiagent settings.