February 09, 2004

Changing my Mind

I change my mind on philosophical matters about once a decade, so even considering that something I have hitherto believed is wrong is quite a rare experience. It’s a pretty esoteric little point to change my mind on though.

For a long time, at least 7 or 8 years I think, I’ve thought it best to model the doxastic states of a rational but uncertain agent not by a single probability function, but by sets of such functions. I’m hardly alone in such a view. Modern adherents have (at various times) included Isaac Levi, Bas van Fraassen and Richard Jeffrey. Like Jeffrey and (I believe) van Fraasen, and unlike Levi, I thought this didn’t make any difference to decision theory. Indeed, I’ve long held a sequences of decision is rationally permissible for an agent characterised by set S iff there is some particular probability function P in S such that no action in the sequence is sub-optimal according to P. I’m thinking of changing that view.

The reason is similar to one given by Peter Walley. He argues that the position I just sketched is too restrictive. The important question for Walley concerns countable additivity. He thinks (as I do) that the arguments from congomerability show that any agent represented by a single probability function should be representd by a countably additive function. But he notes there are sets of merely finitely additive functions such that any agent represented by such a set who follows his decision-theoretic principles will not be Dutch Booked. He argued that such an agent would be rational, so rationality cannot be equivalent to representability by acceptable probability functions.

I never liked this argument for three reasons. First, I didn’t accept his decision principles, which seemed oddly conservative. (From memory it was basically act only if all the probability functions in your representor tell you to act.) Second, I don’t think Dutch Book arguments are that important. I’d rather have completely epistemological arguments for epistemological conclusions. Third, the argument rested on an odd restriction to agents with bounded utility functions, and I don’t really see any reason to restrict ourselves to such agents. So I’d basically ignored the argument up until now. But now I’m starting to appreciate it anew.

I would like to defend as strong a congolmerability principle as possible. In particular I would like to defend the view that if Pr(p | p or q) < x, then for any equinumerous partition of the p-worlds and q-worlds, and function f from the partition of the p-worlds to the partition of the q-worlds, there is one member p’ of the partition of the p-worlds such that Pr(p’ | p’ or f(p’)) < x.

The problem now is what to say about flat probability distributions over continuous regions. At least fairly flat distributions. For it seems they must be necessary. Assume we have an atom with half-life h, and consider the following function g of the time t it actually takes to decay.

g(t) = 1 - 2-t/h

If I’ve done the maths right, for any interval of length l, the objective chance that g(t) falls into l is l. So prior to the process starting up, I better assign probability l to g(t) falling in that interval. The question now is can I extend that to a complete (conditional) probability function in anything like a plausible way, remembering that I want to respect conglomerability. I’m told by people who know a lot more about this stuff than I do that it will be tricky. Let’s leave the heavy lifting maths for another day, because here is where I’m starting to come around to Walley’s view.

Consider the set of all probability functions such that for any interval of length l,

(1) Pr(g(t) is in l) = l.

Some of these will not be conglomerable. Consider, for instance, the function that as well as obeying (1) is such that Pr(g(t) = x | g(t) = x or y) = ½ for any real x, y. That won’t be conglomerable, since Pr(g(t) < ¼) < ½, but obviously there are equinumerous partitions of [0, ¼) and [¼, 1] and a function from one to t’other such that for no x is Pr(g(t) = x | g(t) = x or y) < ½. But there’s a decent enough sense in which the overall set is conglomerable. And maybe, just maybe, that’s enough. It’s certainly enough writing for write now, though I suspect there will be more on this to come.

(By the way, although it may not look like it, some of the ideas here are causally downstream of reflections on Barkley Rosser’s papers, especially this one on the Holmes-Moriarty problem. Rosser’s work is philosophical enough I think that I should probably track him on the papers blog. I’m very grateful to Daniel Davies for pointing out Rosser’s site to me.)

Posted by Brian Weatherson at February 9, 2004 09:17 PM | TrackBack
Comments

I’m not getting your results. Specifically, when h=1, I’m getting the cumulative of g(t) to equal

1/(1-g) for g=minus infinity to 0

And so the probability of an interval from, say, m to n equals

(n-m)/(1-m)(1-n)

and not just the length of an interval (i.e. n-m).

Did you mean g(t) = 1 - 2^(-t/h)? Or have I made a mistake?

Posted by: Bill Carone at February 10, 2004 04:20 PM

Oops I made a mistake. Yep, that’s what I meant.

Posted by: Brian Weatherson at February 10, 2004 04:37 PM

“Some of these will not be conglomerable. Consider, for instance, the function that as well as obeying (1) is such that Pr(g(t) = x | g(t) = x or y) = ½ for any real x, y. That won’t be conglomerable, since Pr(g(t) \

Posted by: Bill Carone at February 10, 2004 09:04 PM

I am pleased that somebody has finally taken notice of my arguments concerning conglomerability! But you have completely misunderstood my theory of decision making: there is nothing ¨conservative¨ about it. In the special case of a precise utility function, my theory, expressed in terms of the credal set (i.e., set of probability measures) representation - which, for me, is only a mathematical representation of more primitive and more directly interpretable measures - says that a decision maker has a preference between two actions if and only if each probability measure in his credal set implies such a preference. If he has no preference either way then he has no reason to choose either action, meaning that he is free to choose either one. Rationality does not constrain his choice in any way. This is quite different from choosing not to act!

I have argued for this view of rationality for 20 years and it has received virtually no support. Isaac Levi has said similar things in some of his writings, but he always goes on to introduce a maximin rule which determines preferences in cases where the decision maker really has no preference. I see no virtue whatever in maximin rules, nor any other rules for determining complete preferences. Incompleteness is, I think, an essential characteristic of rational preferences.

There are strong arguments why utilities should be bounded, but anyway this isn´t essential to my theory. A model with bounded utilities is the simplest way of explaining the behavioural meaning of imprecise probabilities. It could also be done by allowing unbounded utilities, if they are ever needed. It doesn´t affect my arguments for conglomerability.

The concept of coherence in my book, which is the central concept in the conglomerability arguments, isn´t based only on ¨Dutch book¨ arguments. It can be justified epistemologically, as a type of self-consistency that generalises deductive closure.

The arguments in Sections 6.8 and 6.9 of my book have not been addressed by anyone, as far as I know. I think that they are a very strong argument against the ¨robust Bayes / Bayesian sensitivity analysis¨ interpretation of imprecise probabilities. Perhaps they are not completely convincing, if only because they are essentially concerned with infinite spaces, which are an idealisation of really finite problems. There are several other strong arguments against robust Bayes, and it does make a difference to decision theory!

Posted by: Peter Walley at June 28, 2004 10:27 AM
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