3.1. Uniform Probability on
For the reasons given above, we choose for our basic framework a formulation of probability that differs somewhat from Kolmogorov’s. In particular, we will not insist that measurable sets form an algebra, nor will we insist that probabilities be real numbers. We will then show that the conflicts between ZFC and our probability axioms arise, even within this simplified framework. (Another approach to probability, which is more philosophically cautious than Kolmogorov’s, is
qualitative probability. In this formulation, a “not more likely” relation on events, ≦, is axiomatized, rather than a probability function. For one possible axiomatization, see [
11]. We note that our axioms and results can be adapted to this setting.)
Our definitions and axioms are motivated by a prototypical example: selecting a random element from by flipping a fair coin for each ; and associating 0 and 1 to heads and tails, respectively. We refer to this intuitive idea as the fair coin space.
For at least some , the probability that a random element of the fair coin space lies in A seems to have an exact answer. For example, if , then membership in A depends only on the outcomes of two of the coins and thus appears to be .
In the remainder of this section, we present several new definitions and axioms, which are motivated by further considering the fair coin space and exploiting its symmetry (the coins are fair and identical) and independence (the coins do not influence each other).
Definition 1. Let be any total order extending . A minimalist probability space (MPS) is a pair, , , satisfying the conditions below.
- (i)
If is finite, and , then - (ii)
If and , then .
We refer to as the sample space, Σ as the event space and as the probability function. Elements of Σ and are called measurable and non-measurable sets, respectively.
For convenience, we will avoid explicit mention of the set when the meaning is still clear. Thus, expressions such as, “”, should be understood to mean that either both sides of the equation are defined and equal or that they are both undefined.
Let and let for some . Given , whether or not depends only on the restriction of x to I. Therefore, we may reasonably identify “the probability that a random element of is in ” with the “probability that a random element of is in A. In fact, with a slight abuse of notation, we will write to mean .
Notation 1. Let , and let . We will write as a shorthand for .
Notation 2. Let be disjoint, and let . For , we will use to denote the set .
Remark 1. It will frequently be convenient to replace the set with , where N is some countably infinite set. We will call the resulting space an MPS on . Similarly, if I and J are countable sets, we can speak of an MPS on , using the natural identification between this space and .
3.2. Two Axioms
We now introduce two new intuitively appealing axioms. In
Section 4.1 and
Section 4.2, we show that each of these is incompatible with Axiom 4.
Definition 2. An MPS has the Freiling property if the following holds: Let I and J be disjoint subsets of ω. Let . If for every , , then .
We believe that this definition, which is based on Freiling’s Axiom of Symmetry [
6], ought to hold in the fair coin space. To argue this, we will apply a variant of Freiling’s own argument. Suppose
I,
J,
A and
q are as in Definition 2. Since the fair coin space is symmetric, it should not matter in what order we flip the coins when choosing a random element. Therefore, let us start with coins corresponding to elements of
I, followed by those corresponding to elements of
J. Once
has been determined, our hypothesis tells us that the probability that we will choose
such that
is exactly
q. This is true regardless of the value of
x, and hence we may say that it is true
before x is chosen. Thus,
as claimed.
Definition 3. Let N be a countable set. We let denote the group of transformations on generated by functions, , such that either
- (i)
there exists an such that for all , where ⊕ denotes the bitwise XOR operation, or
- (ii)
there exists a permutation such that for all .
A probability symmetry of is an element of . We let · denote the natural action of on .
Definition 4. An MPS on has the dependent symmetry property if the following holds: Let be any bipartition of ω; we will identify with in the natural way. Then , for all , , and .
Again, we will argue that this definition ought to be satisfied by the fair coin space. Fix . Consider randomly choosing an element using two different methods. The first is just that of the fair coin space. For the second, suppose we choose x and y just as before, but if , we replace y with (so the choice of whether to apply does not depend on y). From the point of view of probability, there ought to be no difference between these methods of choosing . Hence, the probabilities that points chosen by each method lie in should be equal if they are defined. This motivates the equality in Definition 4.
Since we believe that the fair coin space is an MPS having the properties given in Definitions 2 and 4, we propose the following axioms.
Axiom 6. There exists an MPS with the Freiling property.
Axiom 7. There exists an MPS with the dependent symmetry property.
Both of these axioms assert the existence of sets with specific properties. Moreover, we have given informal arguments as to why these properties ought to be satisfiable. Hence, our axioms may be viewed as examples of the
maximize principle explored by Maddy in [
4]. This principle essentially states that the set theoretic universe ought to be very “full”, containing as many sets as possible without generating contradictions (e.g., as one gets by declaring
a set).
Remark 2. The usual product measure on satisfies Definition 1 (though not Axioms 6 or 7). Hence, our arguments may be adapted to that setting.