That's fine, but given the parameters of the problem change with the Monty Crawl variant, it's not the same problem, and doesn't invalidate the answer of the base variant.
The problem is that the parameter was unspecified in the original problem. Your answer is equivalent to the shaky answer referred to in the paper. Without knowing that the host selects between 2 goats with 50/50 chance, you cannot give a general answer.
The host might be selecting between two goats, or might be selecting between a goat and a car. Either way, it doesn't matter because we don't get any additional information about whether our original choice was correct. (To clarify, this applies to the original problem, not the Crawl variant, where we either sometimes get definitive information, or sometimes get no information)
Edit: Furthermore, I don't think that author's solution to the Crawl problem is correct. When the host eliminates a door, either you will get information that says you should switch, and you'll win 100% of the time; or you won't get information, and you should still always switch and win 2/3 of the time.
> it doesn't matter because we don't get any additional information about whether our original choice was correct
That's the missing assumption. I would say assuming that people are perfectly random falls into the "standardized test" category.
> you won't get information, and you should still always switch and win 2/3 of the time.
You always get some information, the set of possible results becomes narrower, so saying the probabilities don't change is not sufficient. Not a good idea to discuss the problem in informal language though.
Years ago, the Monty Fall variation was mentioned on a local telnet forum I visited. The "consensus" of the thread was the solution of Monty Fall is the same as that of Monty Hall: switching gives you 2/3 chance to win.
That was when I realized many people just memorize the Monty Hall's solution without understanding it, a.k.a. "standardized tests".
You're probably right, but I enjoyed the effect as text and graphics slid under the header. Originally I was going to have the header and page different colours.
Were there any interesting non-neural approaches? I was wondering whether there is any underlying structure in the ARC tasks that could tell us something about algorithms for "reasoning" problems in general.
Unexplored comes to my mind, it differs from other games with procedural generation in that it generates a graph for the gameplay first and builds the levels around it. It's not necessarily ground breaking, but it has a special feel to it as objects are placed with purpose.
Computer Science becomes MORE interesting as computers become more capable, not less. There are so many things we could be working on, but we still waste so much time on boring libraries, configuration, implementation details that we simply don't get to experiment enough.
Just like nobody programs on punch cards anymore, learning details of a specific technology without deeper understanding will become obsolete. But general knowledge about computer science will become more valuable.
I think the cool part about this is that you can easily build a user interface from physical objects, so you can skip some of the digital frontend and design and focus more on the computational backend. This frees you up for more explorative, improvised coding, which is great for research and art but maybe also many other situations where fixed user interfaces get into the way too much. Based on what they show about their biology lab project, it seems to be surprisingly useful.
I might be confused, but don't 7 guesses actually cover 255 numbers? I think you have to count all nodes in the search tree, not only the leafs, because you can get the correct number before reaching a leaf node.
Or more generally k guesses cover 2^(k+1)-1 numbers,
e.g. with one guess you get the answers correct/high/low, which can cover 3 numbers)
Maybe there is a mistake in my thinking, because this would mean you can cover 127 numbers with 6 guesses so you could not lose the original game.
Edit: My mistake is that you still have to explicitly guess even if you know the precise answer already, so you cannot cover 3 numbers with 1 guess. This means 7 guesses cover 127 numbers.
If the buyer cannot estimate the quality of the product before buying, the sellers will reduce quality or be forced to by competition. Buyers lose trust and the market can collapse.
The Akerloff Market for Lemons paper is really important. It explains so many things, like why people very rarely pay upfront for mobile games or online articles.
Yet people buyer newspaper without having read them…
The reason why people don't pay for online stuff is mostly because we're used to get free stuff online + the fact that online payment remains cumbersome (even moreso since the businesses have all incentives to pish you to a regular payment model instead of a one-shot one). It has nothing to do with information asymmetry.
And that a paper that reads like a parables like this was deemed Nobel-prize worthy tells us more about economics as an academic field than about the paper itself.
The problem there is that the owner of a car that’s good as far as they know (but not a given as a major repair of an older car could be just around the corner) may sell anyway so they can buy a new car even if they think they’re not getting a good deal. But certainly of cars that know they have major not easily detectable problems will be much quicker to sell or trade in. (I know.)
> SSRN provides 1,453,207 preprints and research papers from 1,847,303 researchers in over 65 disciplines.
It's basically like Arxiv, but focused on different fields. The articles may be preprints of peer reviewed articles published in leading journals, or they may be mad ravings uploaded by a crank, or anything in between. Also see wikipedia's article on SSRN[1].
From SSRN's page on Algorithmic Finance[2], the supposed journal (reachable by following the link under the article title):
> The journal archives all papers on SSRN
Note that the journal managing editor and contact is the author of the paper, the contact info appears to be his personal contact info, and all links on the page are dead.
