trentmkelly/LessWrong-43k huggingface dataset:
Making equilibrium CDT into FDT in one+ easy step
by Stuart_Armstrong — 2017-03-21T14:42:58.461Z

In this post, I'll argue that Joyce's equilibrium CDT (eCDT) can be made into FDT (functional decision theory) with the addition of an intermediate step - a step that should have no causal consequences. This would show that eCDT is unstable under causally irrelevant changes, and is in fact a partial version of FDT.

Joyce's principle is:

Full Information. You should act on your time-t utility assessments only if those assessments are based on beliefs that incorporate all the evidence that is both freely available to you at t and relevant to the question about what your acts are likely to cause.

When confronted by a problem with a predictor (such as Death in Damascus or the Newcomb problem), this allows eCDT to recursively update their probabilities of the behaviour of the predictor, based on their own estimates of their own actions, until this process reaches equilibrium. This allows it to behave like FDT/UDT/TDT on some (but not all) problems. I'll argue that you can modify the setup to make eCDT into a full FDT.

Death in Damascus

In this problem, Death has predicted whether the agent will stay in Damascus (S) tomorrow, or flee to Aleppo (F). And Death has promised to be in the same city as the agent (D or A), to kill them. Having made its prediction, Death then travels to that city to wait for the agent. Death is known to be a perfect predictor, and the agent values survival at $1000, while fleeing costs $1.

Then eCDT fleeing to Aleppo with probability 999/2000. To check this, let x be the probability of fleeing to Aleppo (F), and y the probability of Death being there (A). The expected utility is then

1000(x(1-y)+(1-x)y)-x (1)

Differentiating this with respect to x gives 999-2000y, which is zero for y=999/2000. Since Death is a perfect predictor, y=x and eCDT's expected utility is 499.5.

The true expected utility, however, is -999/2000, since Death will get the agent anyway, and the only cost is the trip to Aleppo.

Delegating randomness

The eCDT decision process seems rather peculiar. It seems to allow updating of the value of y dependent on the value of x - hence allow acausal factors to be considered - but only in a narrow way. Specifically, it requires tha...
Book Review: Eisenhorn Trilogy
by Zvi — 2017-03-21T13:39:12.000Z

Spoiler Status: Very mild spoilers before the fold, full spoilers after the fold

I read the Eisenhorn Trilogy on the recommendation of my friend Raymond Arnold, who bought me the first book as a birthday present, presenting it as worth reading and as providing insight into Lovecraftian horror, and as something that would be fun for us to talk about.

I did not love the books as much as he did, but that is to be expected. What I found was a fun romp through numerous action sequences that slowly starts asking interesting questions in between action sequences. In the Warhammer 40K setting, the warp allows travel through space, and also offers lots of other benefits if you are willing to engage with it, but also has the side effect of being full of mind-corrupting demons that drive you into becoming an insane murderous servant of chaos, so the Empire has to deal with people continuously going insane and forming cults that worship chaos demons and try to kill everyone. In response, they have the Inquisition (think the Spanish Inquisition, except the demons are real, have mind control powers and are the most efficient source of physical power) which goes around trying to keep down chaos, including all the Inquisitors who get a little too close to the chaos and turn insane, which happens a lot, and arguing over how engaged with chaos they should be willing to be in order to fight it.

Inquisitors also go around fighting with energy guns and specially engraved swords, killing huge numbers of chaos-enhanced enemies while mostly dodging any attempts to kill them, and looking dope doing it.

There is an obvious story one would tell about such an Inquisitor in this universe. If you’d like to read that story, the books aren’t bad.

Beyond the fold, SPOILERS in the service of discussing the trilogy’s slash universe’s practical and ethical dilemmas.

‘Have you ever noticed that anybody driving slower than you is an idiot, and anyone going faster than you is a maniac?’ – George Carlin

The Inquisitor’s Dilemma

Anyone who engages more with chaos than you is Extremis Diabolus. The punishment is death. If you can’t prove it yet, then for now they’re just a radical. Anyone who engages with chaos less than you is… the guy putting out the proclamation that you are Extremis Diabolus. They then try to kill you, so the effective ...
[Stub] Newcomb problem as a prisoners' dilemma/anti-coordination game
by Stuart_Armstrong — 2017-03-21T10:34:26.708Z

You should always cooperate with an identical copy of yourself in the prisoner's dilemma. This is obvious, because you and the copy will reach the same decision.

That justification implicitly assumes that you and your copy as (somewhat) antagonistic: that you have opposite aims. But the conclusion doesn't require that at all. Suppose that you and your copy were instead trying to ensure that one of you got maximal reward (it doesn't matter which). Then you should still jointly cooperate because (C,C) is possible, while (C,D) and (D,C) are not (I'm ignoring randomising strategies for the moment).

Now look at the Newcomb problem. You decision enters twice: once when you decide how many boxes to take, and once when Omega is simulating or estimating you to decide how much money to put in box B. You would dearly like your two "copies" (one of which may just be an estimate) to be out of sync - for the estimate to 1-box while the real you two-boxes. But without any way of distinguishing between the two, you're stuck with taking the same action - (1-box,1-box). Or, seeing it another way, (C,C).

This also makes the Newcomb problem into an anti-coordination game, where you and your copy/estimate try to pick different options. But, since this is not possible, you have to stick to the diagonal. This is why the Newcomb problem can be seen both as an anti-coordination game and a prisoners' dilemma - the differences only occur in the off-diagonal terms that can't be reached.
Meetup : Melbourne Social Meeetup: March
by Maelin — 2017-03-21T09:17:04.809Z

Discussion article for the meetup : Melbourne Social Meeetup: March

WHEN:
24 March 2017 06:30:00PM (+1100)

WHERE:
The Bull and Bear Tavern, Flinders Lane, Melbourne

Come along for this month's Social Meetup, now on the exciting new schedule of the fourth Friday of the month!

FB event page: https://www.facebook.com/events/463034997361085/

Social meetups are informal get-togethers where we chat about topics of interest and have a couple of drinks together.

WHEN? Friday March 24, 18:30 until late. Don't worry about being on time, though - it's fine to rock up whenever.

WHERE? The Bull & Bear Tavern, on Flinders Lane (just a short walk from Flinders St Station).

FOOD? The B&B does reasonable traditional pub food and we usually share a few plates of wedges. For those who stay late, we often go for a late night meal at around 11pm

CONTACT? Any issues on the night, call or text Richard on 0421231789

Discussion article for the meetup : Melbourne Social Meeetup: March
[Error]: Statistical Death in Damascus
by Stuart_Armstrong — 2017-03-20T19:17:10.859Z

Note: This post is in error, I've put up a corrected version of it here. I'm leaving the text in place, as historical record. The source of the error is that I set Pa(S)=Pe(D) and then differentiated with respect to Pa(S), while I should have differentiated first and then set the two values to be the same.

Nate Soares and Ben Levinstein have a new paper out on "Functional Decision theory", the most recent development of UDT and TDT.

It's good. Go read it.

This post is about further analysing the "Death in Damascus" problem, and to show that Joyce's "equilibrium" version of CDT (causal decision theory) is in a certain sense intermediate between CDT and FDT. If eCDT is this equilibrium theory, then it can deal with a certain class of predictors, which I'll call distribution predictors.

Death in Damascus

In the original Death in Damascus problem, Death is a perfect predictor. It finds you in Damascus, and says that it's already planned it's trip for tomorrow - and it'll be in the same place you will be.

You value surviving at $1000, and can flee to Aleppo for $1.

Classical CDT will put some prior P over Death being in Damascus (D) or Aleppo (A) tomorrow. And then, if P(A)>999/2000, you should stay (S) in Damascus, while if P(A)<999/2000, you should flee (F) to Aleppo.

FDT estimates that Death will be wherever you will, and thus there's no point in F, as that will just cost you $1 for no reason.

But it's interesting what eCDT produces. This decision theory requires that Pe (the equilibrium probability of A and D) be consistent with the action distribution that eCDT computes. Let Pa(S) be the action probability of S. Since Death knows what you will do, Pa(S)=Pe(D).

The expected utility is 1000.Pa(S)Pe(A)+1000.Pa(F)Pe(D)-Pa(F). At equilibrium, this is 2000.Pe(A)(1-Pe(A))-Pe(A). And that quantity is maximised when Pe(A)=1999/4000 (and thus the probability of you fleeing is also 1999/4000).

This is still the wrong decision, as paying the extra $1 is pointless, even if it's not a certainty to do so.

So far, nothing interesting: both CDT and eCDT fail. But consider the next example, on which eCDT does not fail.

Statistical Death in Damascus

Let's assume now that Death has an assistant, Statistical Death, that is not a prefect predictor, but is a perfect distribution predictor. It can predict the distribution of your actions, but not your actual decis...
Open thread, Mar. 20 - Mar. 26, 2017
by MrMind — 2017-03-20T08:01:08.320Z

Notes for future OT posters:

1. Please add the 'open_thread' tag.

2. Check if there is an active Open Thread before posting a new one. (Immediately before; refresh the list-of-threads page before posting.)

3. Open Threads should start on Monday, and end on Sunday.

4. Unflag the two options "Notify me of new top level comments on this article" and "Make this post available under..." before submitting.
Meetup : Games in Kocherga club: Fallacymania, Tower of Chaos, Scientific Discovery
by Alexander230 — 2017-03-19T13:51:42.515Z

Discussion article for the meetup : Games in Kocherga club: Fallacymania, Tower of Chaos, Scientific Discovery

WHEN:
29 March 2017 07:40:00PM (+0300)

WHERE:
Moscow, B.Dorogomilovskaya, 5-2

Welcome to Moscow LW community makeshift games! In that games, some rationality skills are involved, so you can practise while you playing!

Fallacymania: it is a game where you guess logical fallacies in arguments, or practise using logical fallacies yourself (depending on team in which you will be).

Tower of Chaos: funny game with guessing the rules of human placement on a Twister mat.

Scientific Discovery: modified version of Zendo with simultaneous turns for all players.

Details about the games: http://goo.gl/Mz2i94

Come to antikafe "Kocherga", ul.B.Dorogomilovskaya, 5-2. The map is here: http://kocherga-club.ru/#contacts . Nearest metro station is Kievskaya. If you are lost, call Sasha at +7-905-527-30-82.

Games begin at 19:40, the length is 3 hours.

Discussion article for the meetup : Games in Kocherga club: Fallacymania, Tower of Chaos, Scientific Discovery
On Automoderation
by Zvi — 2017-03-19T02:56:58.000Z

Follow Up to: Trio Walks, Duo Talks

Response to: Automoderation (Ferocious Truth)

Hat Tip: Automoderation (Agenty Duck)

In my post Trio Walks, Duo Talks I laid out the thesis that the key to a high-quality discussion with more than two participants is to organize the group such that it takes on many of the features of a two-person conversation, because the back and forth between two parties allows complex ideas and paths to be considered and the discussion kept on track, whereas conversations not so organized render this extraordinarily difficult. One implication of this is that a good interaction relies on situational inequality. At the end, I did note that group discussions sometimes need to be run with an emphasis on equality, so everyone can contribute and feel included, but that the results tend to be disappointing.

The Columbus rationalists have developed a system designed to maximize what is good about an equality-based conversation. The system is well-thought out, well-presented by J Thomas Moros and has many elements that seem correct to me, so please do read the whole thing. I especially appreciate the spirit in which it is offered:

This post was written in the hope that other rationalist communities will find it useful and spread and improve the system. Take whatever parts seem useful and apply them as seems best.

Write-ups of such systems are valuable even if the systems themselves prove not to be, because they provide insight into what people are thinking about and trying. I want to see more like this!

Their write-up starts out with its justifying thesis that equality is the path to truth:

Group discussions can easily become unwieldy. Certain individuals have a tendency to dominate the conversation, limiting others’ ability to contribute. When the goal is collaborative truth seeking, this is counter productive. Those who are excluded from the discussion may be exactly the ones with the necessary insights to advance the dialogue toward the truth.

…

Automoderation embodies a wait rather than an interrupt culture. Interrupt culture may be fine for a causal fun conversation, but collaborative truth seeking is aided by a wait culture.

There are many bold claims here that I do not agree with, but I approve of stating such assumptions up front and explicitly even when justification is not provided, as this makes it clear where the system is coming from....
Self-fulfilling values of time
by KatjaGrace — 2017-03-18T22:00:22.000Z

How much do you think your time is worth?

Let’s say you are pretty unsure, but you guess ‘hardly anything’. So when you see opportunities to turn your time into a little bit of value, you naturally jump at them. You offer to clean your friend’s car for her, because it’s a way of saving ten dollars for like an hour of your time, which would otherwise be put to a worse use. You put a lot of attention into finding good shopping deals and learning how to make cheaper meals. And in between all this, you don’t mind cutting down your work hours to enjoy life, because losing an hour of productivity is worth less than the popcorn. Sometimes you do reassess the value of your time, by thinking about your second best options for spending it. For instance, if you didn’t clean your friend’s car, what would you have been doing? Probably making your own granola, which is worth something, but doesn’t matter much. So you learn that you were right: your time is not worth much.

But let’s say instead that you guess that your time is worth a lot. You then shamelessly skip over any task that isn’t also worth a lot. You jump at opportunities to spend dollars to save minutes, and buy whatever is convenient and doesn’t get in the way of the real work. If a new opportunity appears, you compare it to the next best thing you could be doing, and since that is something awesome (or you wouldn’t be doing it), few opportunities are good enough to take. So it turns out that you were right: your time is worth a lot.

This probably shouldn’t happen to an ideal agent, but I think it probably does happen to humans. I am curious whether this is a familiar phenomenon to others.

You might think, if you guess your time is not worth much, won’t you correct it later if it is, when you see the more amazing opportunities on the table? In practice maybe not, because you (and others) partly assess which things you can do by the current value of your time (e.g. maybe I can see that it is valuable to start an awesome startup but I assume it is not an opportunity for *me* because I am usually peeling carrots or something, and am not even amazing at that). Also you don’t necessarily hear about high value opportunities if you are doing low value activities. Also, maybe you hear about fewer things altogether if you stop at the first opportunity to turn time into peanuts and turn your attention to running that pr...
Attractor Theory: A Model of Minds and Motivation
by  — 2017-03-18T03:12:50.640Z

Attractor Theory: A Model of Minds and Motivation

[Epistemic status: Moderately strong. Attractor Theory is a model based on the well-researched concept of time-inconsistent preferences combined with anecdotal evidence that extends the theory to how actions affect our preferences in general. See the Caveats at the end for a longer discussion on what this model is and isn’t.]

<Cross-posted from mindlevelup>

Introduction:

I’ve thinking about minds and motivation somewhat on/off for about a year now, and I think I now have a model that merges some related ideas together into something useful. The model is called Attractor Theory, and it brings together ideas from Optimizing Your Mindstate, behavioral economics, and flow.

Attractor Theory is my attempt to provide a way of looking at the world that hybridizes ideas from the Resolve paradigm (where humans Actually Try and exert their will) and the “click-whirr” paradigm (where humans are driven by “if-then” loops and proceduralized habits).

As a brief summary, Attractor Theory basically states that you should consider any action you take as being easier to continue than to start, as well as having meta-level effects on changing your perception of which actions feel desirable.

The Metaphor:

Here’s a metaphor that provides most of the intuitions behind Attractor Theory:

Imagine that you are in a hamster ball:

As a human inside this ball, you can kinda roll around by exerting energy. But it’s hard to do so all of the time — you’d likely get tired. Still, if you really wanted to, you could push the ball and move.

These are Utilons. They represent productivity hours, lives saved, HPMOR fanfictions written, or anything else you care about maximizing. You are trying to roll around and collect as many Utilons as possible.

But the terrain isn’t actually smooth. Instead, there are all these Attractors that pull you towards them. Attractors are like valleys, or magnets, or point charges. Or maybe electrically charged magnetic valleys. (I’m probably going to Physics Hell for that.)

The point is that they draw you towards them, and it’s hard to resist their pull.

Also, Attractors have an interesting property: Once you’re being pulled in by one, this actually modifies other Attractors. This usually manifests by changing how stro

...
Restaurant Guide 2: Pizza
by Zvi — 2017-03-17T23:22:45.000Z

Continuation From: Restaurant Guide 1

Epistemic Status: Hungry

Pizza is a special case that is worthy of its own attention, so this section will do that. There isn’t as much of a boarder thesis here, and the judgments are more subjective. Part 1 was about more than just restaurants, but Part 2 is almost entirely about pizza.

Pizza has distinct sub-genres. I will refer to them into six: New York, Italian, NYC-Italian Hybrid, Chicago, Acceptable Chain and Not Pizza.

New York Style

Also known as real pizza.

Reviews of New York style places are unusually unreliable. People evaluate on all the wrong things, so you can’t count on even quite high ratings to signal great pizza (they do reliably mean good service and solid pizza).

Go in and look at the pies! One of the great advantages of New York style is that one look tells you almost everything, and any self-respecting place will have pizzas on display for your perusal. Look at the plain pie even if you plan to order toppings, as it contains the most information.

Notice whether the pizza is fresh. If the pizza is right out of the oven, that’s pretty great. If it has been lying around for hours, it should be obvious, and that is terrible. New York pizza can survive reheating (Sicilian/Grandma tends to survive best), and still be acceptable eating in an emergency, but it is still never the same afterwards. Reheating any pizza is a tragedy, and a strong argument against getting toppings on individual slices, since they must then almost always be reheated. If you do decide to order plain slices, there is a reasonably large range where it is correct to stop the place from reheating your slices and take them as is.

The plain pizza not being hot means the place can’t sell plain pizza, which is basically death.

Next you want to look at the details. There is no substitute for experience in knowing how to read those details, but some of them are easy to spell out. The biggest thing to look for is the color and texture patterns, which should be diverse. The pizza should feel alive. You want a richness of layers, with uneven heights that are not crust bubbles (bubbles are fine, but not what you are looking for here) representing an organic mixing of elements. You want to see a rich tapestry of colors, a blending of tomato sauce and cheese, and the primary color should be red rather than white. You want to see th...
Dominant stochastic markets
by Vanessa Kosoy — 2017-03-17T12:16:55.000Z

% operators that are separated from the operand by a space

% operators that require brackets

% operators that require parentheses

% Paper specific

We generalize the formalism of dominant markets to account for stochastic "deductive processes," and prove a theorem regarding the asymptotic behavior of such markets. In a following post, we will show how to use these tools to formalize the ideas outlined here.

Appendix A contains the key proofs. Appendix B contains the proofs of technical propositions used in Appendix A, which are mostly straightforward. Appendix C contains the statement of a version of the optional stopping theorem from Durret.

##Notation

Given X a topological space:

P(X) is the space of Borel probability measures on X equipped with the weak* topology.

C(X) is the Banach space of continuous functions X→R with uniform norm.

B(X) is the Borel σ-algebra on X.

U(X) is the σ-algebra of universally measurable sets on X.

Given μ∈P(X), suppμ denotes the support of μ.

Given X and Y measurable spaces, K:Xmk−→ Y is a Markov kernel from X to Y. For any x∈X, we have K(x)∈P(Y). Given μ∈P(X), μ⋉K∈P(X×Y) is the semidirect product of μ and K and K∗μ∈P(Y) is the pushforward of μ by K.

Given X, Y Polish spaces, π:X→Y Borel measurable and μ∈P(X), we denote μ∣π the set of Markov kernels K:Ymk−→X s.t. π∗μ⋉K is supported on the graph of π and K∗π∗μ=μ. By the disintegration theorem, μ∣π is always non-empty and any two kernels in μ∣π coincide π∗μ-almost everywhere.

##Results

The way we previously laid out the dominant market formalism, the sequence of observations (represented by the sets {Xi}) was fixed. To study forecasting, we instead need to assume this sequence is sampled from some probability measure (the true environment).

For each n∈N, let On be a compact Polish space. On represents the space of possible observations at time n. Denote

Yn:=∏m<nOm

Given n≤m, πnm:Ym→Yn denotes the projection mapping and πn:=πn,n+1. Denote

X=∞∏n=0On

X is a compact Polish space. For each n∈N we denote πnω:X→Yn the projection mapping. Given y∈Yn, we denote Xy:=π−1nω(y), a closed subspace of X. Given n∈Z and x∈X, we denote x(n):=πmax(n,0)ω(x).

#Definition 1

A market is a sequence of mappings {Mn:Yn→P(X)}n∈N s.t.

Each Mn is measurable w.r.t. U(Yn) and B(P(X)).

For any y∈Yn, suppMn(y)⊆Xy.

As before, we define the space of trading strat

...