Bluff (poker)

A player making a pure bluff believes they can win the pot only if all opponents fold.

For example, suppose that after all the cards are out, a player holding a busted drawing hand decides that the only way to win the pot is to make a pure bluff.

In some cases a player may be on a draw but with odds strong enough that they are favored to win the hand.

Several game circumstances may decrease the probability of being called (and increase the profitability of the bluff): The opponent's current state of mind should be taken into consideration when bluffing.

Under certain circumstances external pressures or events can significantly impact an opponent's decision making skills.

For example, a player might use the colors of their hidden cards, the second hand on their watch, or some other unpredictable mechanism to determine whether to bluff.

If Worm does bluff in this situation, they are giving Mike 2-to-1 pot odds to call with their two pair (10's and 2's).

Say in this example, Worm decides to use the second hand of their watch to determine when to bluff (50% of the time).

The purpose of optimal bluffing frequencies is to make the opponent (mathematically) indifferent between calling and folding.

Optimal bluffing frequencies are based upon game theory and the Nash equilibrium, and assist the player using these strategies to become unexploitable.

In these situations, a player makes a play that should not be profitable unless an opponent misjudges it as being made from a position capable of justifying it.

Since a successful bluff requires deceiving one's opponent, it occurs only in games in which the players conceal information from each other.

In games like chess and backgammon, both players can see the same board and so should simply make the best legal move available.

Examples include: Evan Hurwitz and Tshilidzi Marwala developed a software agent that bluffed while playing a poker-like game.

The agent was able to learn to predict its opponents' reactions based on its own cards and the actions of others.

In economics, bluffing has been explained as rational equilibrium behavior in games with information asymmetries.

For instance, consider the hold-up problem, a central ingredient of the theory of incomplete contracts.