If you have ever wondered why you
never seem to win at skill-based games such as poker or chess, there might be a
very good reason. A University of Manchester physicist has discovered that some
games are simply impossible to fully learn, or too complex for the human mind
to understand. Researchers ran thousands of simulations of two-player games to
see how human behaviour affects their decision-making. In simple games with a
small number of moves, such as Noughts and Crosses the optimal strategy is easy
to guess, and the game quickly becomes uninteresting. However, when games
became more complex and when there are a lot of moves, such as in chess, the
board game Go or complex card games, the academics argue that players' actions
become less rational and that it is hard to find optimal strategies.
This research could also have
implications for the financial markets. Many economists base financial
predictions of the stock market on equilibrium theory -- assuming that traders
are infinitely intelligent and rational. This, the academics argue, is rarely
the case and could lead to predictions of how markets react being wildly
inaccurate. Much of traditional game theory, the basis for strategic
decision-making, is based on the equilibrium point -- players or workers having
a deep and perfect knowledge of what they are doing and of what their opponents
are doing. Equilibrium is not always the right thing you should look for in a
game. Preliminary results suggest that as the number of players increases, the
chances that equilibrium is reached decrease. Thus for complicated games with
many players, such as financial markets, equilibrium is even less likely to be
the full story.
More information: