Mathematical aspects of Pascal's wagerRebuttal of Pascal's wager |
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Pascal's wager draws its arguments from the framework of games of chance. The mathematical model of game theory Many contemporary commentators formalise Pascal's wager with game theory, the foundations of which were described in the 1920s by Ernst Zermelo and developed by Oskar Morgenstern and John von Neumann in 1944. As Pascal died in 1662, it is an anachronism to interpret Pascal's wager by means of game theory, and there is a great risk of betraying his thought. Moreover, infinity is treated as an entity, which poses problems of realism that we will discuss later. Huygens' mathematical modelThe first person to successfully pursue Pascal's work on games of chance was the Dutch mathematician and physicist Christiaan Huygens. In the period 1655 - 1657, while Pascal was still alive, he generalised Pascal's method to the case where the transition probabilities are unevenly distributed. He was also the first to use the term expectation (Hoffnung). It is this historical way of formalising Pascal's wager that seems relevant to me and that I have retained. As far as infinity is concerned, it will not be treated as an entity, but as a limit. The example of roulette wheel: bet on a single number![]() The play mat has 37 squares numbered from 0 to 36. Playing "single" consists in placing the bet, noted b, on a single square. If the chosen number comes up, the player wins 36 times the bet, which is the gross winnings from which the bet must be deducted to obtain the net winning. In our model, we do not take into account what the player usually leaves for the casino staff. The random variable of the game is \[ \small \begin{equation*} \left\{ \begin{array}{ccc} −b + 36b = 35b & \text{with a prob. of } & 1/37\\ -b & \text{ with a prob. of } & 36/37 \end{array} \right. \end{equation*} \]The mathematical expectation of the net winning is \[ \begin{equation*} \begin{aligned} E &= 35 b \cdot \frac{1}{37} + (−b) \cdot \frac{36}{37}\\ &= (-\frac{1}{37}) \cdot b \end{aligned} \end{equation*} \]This means that, over a large number of games, the player loses on average 1/37 of his bets to the casino. It is a game with negative mathematical expectation. The formula for mathematical expectationTo generalize, let us consider a game of chance in which, for a bet b, you can get the winning w with a probability p. The random variable is \[ \begin{equation*} \left\{ \begin{array}{ccc} -b + w & \text{with a prob. of } & p\\ -b & \text{ with a prob. of } & 1-p \end{array} \right. \end{equation*} \]The mathematical expectation of the net winning is \[ \begin{align} E &= (-b+w) \cdot p + (−b) \cdot (1-p)\\ &= -b + w \cdot p \end{align} \]Remember \[ E = -b + w \cdot p \]From the latter formula is derived the expression of the probability : \[ p = \frac{E+b}{w} \qquad \text{ where } w>0 \]Conditions 0 ≤ p ≤ 1 result in 0 ≤ (E+b) ≤ w The case of fair gamesIf the mathematical expectation of the net winning is zero, the game is said to be fair. The probability of winning is then p = b/w. For example, by betting 1 €, it is a fair game to be able to win 1000 € with a probability of 1/1000; in another game, by betting 1 €, it is fair to be able to win 1,000,000 € with a probability of 1/1,000,000. When the winning is huge, the probability of winning is tiny. With a constant bet, if the winning tends towards infinity, the probability of winning tends towards 0: \[ p = \lim_{w\to\infty} \frac{b}{w} = 0\]Case of games with high mathematical expectationIf the mathematical expectation of the net winning is positive, a generous sponsor is needed to contribute to the financing of the winning. While the players to whom the wager is addressed wait for a mathematical expectation close to zero, i.e. a game not too biased, believers imagine an immense mathematical expectation. Suppose for example that E is worth a billion times the bet. Since (E+b) is constant, the limit probability remains zero: \[ p = \lim_{w\to\infty} \frac{E+b}{w} = 0\]i.e. with a constant bet, however great the mathematical expectation, when the winning tends towards infinity, the probability of winning tends towards 0. To be convinced of this, consider the following sequence of winnings: 10(E+b), 100(E+b), 1000(E+b), 10000(E+b), and so on. The corresponding probabilities will have the values :
To obtain this result, it is not necessary for the mathematical expectation to be constant, but only for its absolute value to be capped by an upper bound, i.e. there is a number E such that, for all winnings, In the end, Pascal's wager is unfounded. DiscussionQuestion I still have a doubt. For me, the probability that God exists may be small, but positive.Answer Let's take a specific Church that offers you salvation on the condition that you pay it, for example, €100 per month. The probability that this is true is small, but one can have a doubt and judge that this probability is not nil. If you do not make the payments, it is because you do not support to the end the idea of taking into account events of low probability. What is the reason for this? Presumably because it is impossible to take into account everything that might possibly be possible. You have to decide what is serious and credible, and reject everything else. Personally, I don't have the kind of doubt that your question evokes, because I firmly believe that I am not endowed with immortality. So Pascal's wager is pointless. Question Could it be envisaged that, with w tending towards infinity, E also tending towards infinity?Answer
Question What to answer to "The probability of obtaining an infinite winning may be close to 0, but it does not tend towards 0! It is a real positive fixed." ?Answer
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