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Comment author: MattG 26 September 2015 07:51:25AM 0 points [-]

I'm still getting a weird big screen with a tiny little text area at the bottom. Is that how it's supposed to be?

Comment author: Kaj_Sotala 29 September 2015 03:56:15PM 0 points [-]

Nope. :(

Comment author: gjm 27 September 2015 04:07:43PM 0 points [-]

I'm finding the game ... not fun. Here are some reasons.

  • The notation for "Bayes nodes" is confusing and figuring out what it's saying requires more conscious thought than I really want to be putting into a game like this.
  • There's this menu where I have to choose "go to lectures", "study in the library", or "hang out with friends" all the time -- except that only one choice is actually ever available (so far, at least).
  • There's too much now-press-space, somehow.
  • In the actual node-guessing game that's the main activity, you usually get to inspect about one node per lecture on average. That's not enough to make it very interesting. (Also: if the idea is to teach people about separation, so that they can figure out when knowing the state of one node means that learning X doesn't tell you anything about Y, wouldn't it be better if that situation were to arise more often?)
  • It doesn't feel to me as if any sort of highbrow analysis of the networks provides a substantial advantage, which is a shame if the idea is to make people learn to do it. On the other hand ...
  • So far I've played three or four games and been rejected by the academy about halfway through every time. So maybe there are strategic lessons I haven't learned yet. Or maybe it's just that success is too dependent on luck?
Comment author: Kaj_Sotala 29 September 2015 03:55:58PM 0 points [-]

Thanks for the feedback, I agree with a lot of your criticisms.

Re: the difficulty: just played the game and thrice and failed on each attempt. Huh, I remember that when I was trying to get the difficulty right before releasing it, I managed to get pretty reliably to the last stages, if not beat it. Looks like I notched the difficulty too up, when it used to be too easy at first.

Comment author: Lumifer 23 September 2015 02:47:05PM 1 point [-]

Who's your target audience/guinea pigs? Most normal people would run away screaming after seeing the "This survey tests your understanding of d-separation in Bayesian networks" part.

Comment author: Kaj_Sotala 29 September 2015 03:35:51PM 0 points [-]

Well, I was hoping the "don't worry if you don't understand the questions" bit to help avoid the running away effect. :)

Comment author: Bobertron 27 September 2015 07:25:52PM 2 points [-]

I actually really like that you have to spend a resource to learn new information and that the score is dependent on luck. I.e. you use limited resources to optimize the gamble you are making. That seems like a very good description of how life works, only, it's all transparent and quantified in your game.

Some suggestions:

  • In the tutorial, why do I first get to read a description of a picture and then I'm presented with the picture? Obviously, it should be the other way around.
  • You should be able to progress the text by mouse.
  • It should be easier to distinguish new text from old. I think in visual novels, the text box never "scrolls". If the new text doesn't fit into the text box, or to make a new paragraph, the text box is cleared. You could make separate textboxes for the current message and the history.
  • The confusing notation is a real distraction and zaps away a lot of the potential fun. Understanding the notation actually seems more interesting than winning the game, but I have too little information to understand it, which leads to frustration. Why are there two big boxes with normal nodes? Why do normal nodes have all those boxes instead of simple bar that shows the probability? Why do bayes-nodes have all those rows instead of just two bars? What are there grey bars? How do 'and' and 'or' nodes work? I would think that one input corresponds to the vertical division and one input to the horizontal division. It should be more obvious which node is which (by having the input into that side of the box). The connections of nodes did not have arrows. If I understood the game correctly, that would help distinguish inputs from outputs.
  • The effect of clicking on one node shouldn't be instant. At first, it should probably go step by step: You click on a node and reveal it's truth-value (some text appears explaining which node changed and why). Press a key -> the next affected node gets updated. Until affected nodes are updated. Later you don't have to click, there is a small pause between each change. That way you could see the effect of measuring a node and understand why the effect was the way it was, instead of ... trying to work that information out for yourself with only being able to see the aftermath.
  • You should make it more linear. Put the tutorial and the main game into one. I don't see the use of this decision between introductory and intermediate psychology.
  • Have the player start out with much simpler networks and infinite energy.
  • Introduce new types of nodes during the game, not all at once in the tutorial. Every time you introduce something new, go back to simple networks with unlimited energy.

Of those, explaining or simplifying the notation seems the most important to me.

Comment author: Kaj_Sotala 29 September 2015 03:35:00PM 0 points [-]

Thanks! I agree with all of your points and had considered implementing many of them myself: unfortunately, while working on this project I learned that I hate UI programming, and finally got to the point where I just wanted to put out a not-too-totally-horrible prototype and be done with it. :(

The source code was written to employ a bit of an MVC architecture, with the intention of making it easier for other people to implement a better UI afterwards... but in retrospect just rewriting the whole thing under a better platform than Java might be the best approach, if anyone wants to do that.

Comment author: MattG 23 September 2015 08:12:31PM 1 point [-]

Awesome! What's the download link without retaking the survey?

Comment author: Kaj_Sotala 24 September 2015 06:33:43PM 0 points [-]

http://kajsotala.fi/Thesis/BayesGame.jar / http://kajsotala.fi/Thesis/BayesGameWindows.rar

(posting direct links here rather than send a PM to minimize trivial inconveniences for anyone else who might have taken the survey already, but if you're reading this and haven't, please do take the survey before playing - and then answer the posttest survey after playing, too :) )

Comment author: DanielLC 23 September 2015 02:53:33AM 1 point [-]

I tried it on Ubuntu. The game is practically unplayable. I only see the last line of the text unless I scroll, and most of the bottom box is covered. Is the text supposed to be so huge?

Comment author: Kaj_Sotala 23 September 2015 09:50:56AM 0 points [-]

I've just uploaded a new version that lets you choose a lower resolution setting (and thus a smaller font size). Sorry about that.

Comment author: Raziel123 23 September 2015 05:06:07AM 0 points [-]

Ok, I wanted to play it, but the word are too big and/or the textbox is too small. graphics don't run well, and it really needs an exit button. I'm using windows 8. other than that, I think the idea is great.

Comment author: Kaj_Sotala 23 September 2015 09:50:49AM 1 point [-]

I've just uploaded a new version that lets you choose a lower resolution setting (and thus a smaller font size). Sorry about that.

Comment author: V_V 19 September 2015 09:51:06PM *  0 points [-]

There seems to be no obvious reason to assume that the probability falls exactly in proportion to the number of lives saved.

It is an assumption to make asymptotically (that is, for the tails of the distribution), which is reasonable due to all the nice properties of exponential family distributions.

If GiveWell told me they thought that real-life intervention A could save one life with probability PA and real-life intervention B could save a hundred lives with probability PB, I'm pretty sure that dividing PB by 100 would be the wrong move to make.

I'm not implying that.


As a simple example, if you model the number of lives saved by each intervention as a normal distribution, you are immune to Pascal's Muggings. In fact, if your utility is linear in the number of lives saved, you'll just need to compare the means of these distributions and take the maximum. Black swan events at the tails don't affect your decision process.

Using normal distributions may be perhaps appropriate when evaluating GiveWell interventions, but for a general purpose decision process you will have, for each action, a probability distribution over possible future world state trajectories, which when combined with an utility function, will yield a generally complicated and multimodal distribution over utility. But as long as the shape of the distribution at the tails is normal-like, you wouldn't be affected by Pascal's Muggings.

Comment author: Kaj_Sotala 20 September 2015 11:38:36AM 0 points [-]

But it looks like the shape of the distributions isn't normal-like? In fact, that's one of the standard EA arguments for why it's important to spend energy on finding the most effective thing you can do: if possible intervention outcomes really were approximately normally distributed, then your exact choice of an intervention wouldn't matter all that much. But actually the distribution of outcomes looks very skewed; to quote The moral imperative towards cost-effectiveness:

DCP2 includes cost-effectiveness estimates for 108 health interventions, which are presented in the chart below, arranged from least effective to most effective [...] This larger sample of interventions is even more disparate in terms of costeffectiveness. The least effective intervention analysed is still the treatment for Kaposi’s sarcoma, but there are also interventions up to ten times more cost-effective than education for high risk groups. In total, the interventions are spread over more than four orders of magnitude, ranging from 0.02 to 300 DALYs per $1,000, with a median of 5. Thus, moving money from the least effective intervention to the most effective would produce about 15,000 times the benefit, and even moving it from the median intervention to the most effective would produce about 60 times the benefit.

It can also be seen that due to the skewed distribution, the most effective interventions produce a disproportionate amount of the benefits. According to the DCP2 data, if we funded all of these interventions equally, 80% of the benefits would be produced by the top 20% of the interventions. [...]

Moreover, there have been health interventions that are even more effective than any of those studied in the DCP2. [...] For instance in the case of smallpox, the total cost of eradication was about $400 million. Since more than 100 million lives have been saved so far, this has come to less than $4 per life saved — significantly superior to all interventions in the DCP2.

Comment author: V_V 18 September 2015 01:49:04PM *  -1 points [-]

I'd say that if you assign a 10^-22 probability to a theory of physics that allows somebody to create 10^100 happy lives depending on your action, then you doing physics wrong.

If you assign probability 10^-(10^100) to 10^100 lives,10^-(10^1000) to 10^1000 lives, 10^-(10^10000) to 10^10000 lives, and so on, then you are doing physics right and you will not fall for Pascal's Mugging.

Comment author: Kaj_Sotala 19 September 2015 05:23:17PM *  1 point [-]

There seems to be no obvious reason to assume that the probability falls exactly in proportion to the number of lives saved.

If GiveWell told me they thought that real-life intervention A could save one life with probability PA and real-life intervention B could save a hundred lives with probability PB, I'm pretty sure that dividing PB by 100 would be the wrong move to make.

Comment author: entirelyuseless 18 September 2015 07:55:36PM 1 point [-]

I agree that bounded utility implies that utility is not linear in human lives or in other similar matters.

But I have two problems with saying that we should try to get this property. First of all, no one in real life actually acts like it is linear. That's why we talk about scope insensitivity, because people don't treat it as linear. That suggests that people's real utility functions, insofar as there are such things, are bounded.

Second, I think it won't be possible to have a logically coherent set of preferences if you do that (at least combined with your proposal), namely because you will lose the independence property.

Comment author: Kaj_Sotala 19 September 2015 05:12:50PM 0 points [-]

I agree that, insofar as people have something like utility functions, those are probably bounded. But I don't think that an AI's utility function should have the same properties as my utility function, or for that matter the same properties as the utility function of any human. I wouldn't want the AI to discount the well-being of me or my close ones simply because a billion other people are already doing pretty well.

Though ironically given my answer to your first point, I'm somewhat unconcerned by your second point, because humans probably don't have coherent preferences either, and still seem to do fine. My hunch is that rather than trying to make your preferences perfectly coherent, one is better off making a system for detecting sets of circular trades and similar exploits as they happen, and then making local adjustments to fix that particular inconsistency.

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