Evaluating the Performance of Presumed Payoff Perfect Information Monte Carlo Sampling Against Optimal Strategies

A very recent algorithm shows search of games of imperfect information has been around how both theoretical problems can be fixed (Lisý, Lanctot, for many years. The approach is appealing, for a number of and Bowling 2015), but has yet to be applied to large games reasons: it allows the usage of well-known methods from typically used for search. More recently overestimation of perfect information games, its complexity is magnitudes MAX's knowledge is also dealt with in the field of general lower than the problem of weakly solving a game in the game play (Schofield, Cerexhe, and Thielscher 2013). To the sense of game theory, it can be used in a justin-time manner best of our knowledge, all literature on the deficiencies of (no precalculation phase needed) even for games with PIMC concentrates on the overestimation of MAX's knowledge.