  In imperfect information games (e.g. Bridge, Skat, Poker), one of the
fundamental considerations is to infer the missing information while at the
same time avoiding the disclosure of private information. Disregarding the
issue of protecting private information can lead to a highly exploitable
performance. Yet, excessive attention to it leads to hesitations that are no
longer consistent with our private information. In our work, we show that to
improve performance, one must choose whether to use a player's private
information. We extend our work by proposing a new belief distribution
depending on the amount of private and public information desired. We
empirically demonstrate an increase in performance and, with the aim of further
improving performance, the new distribution should be used according to the
position in the game. Our experiments have been done on multiple benchmarks and
in multiple determinization-based algorithms (PIMC and IS-MCTS).
