Oh, sorry to hear that happened to you. I’ve had that happen to me myself on other “learn X” platforms, and it is extremely frustrating, although it never happened to me on code academy (back when I was just learning Python, I actually started using code academy after an experience like that somewhere else).
In terms of strength, I felt Code Academy had pretty decent coverage of the fundamentals (things like syntax, whitespacing, if statements, for loops, etc.) and good pacing (didn’t go too fast or too slow for the most part). It doesn’t take you beyond them, but it really isn’t meant to.
And hacker rank is sort of the graduated counterpart to it, where when you know the fundamentals, you can stretch your muscles there with various problems.
But if Code Academy isn’t working for you, I’d urge you to explore other options. I’ve heard decent things about Solo Learn (free), and of course there’s lots of paid options like Pluralsight and Code School (Pluralsight has been endorsed by a number of team-managing devs I know in terms of being worth it to get people up to speed on something new).
Maybe I’m misunderstanding the word “how”. I was thinking it was a description of a sequence of steps and required components at each step to achieve the result of something (like growth).
Producing the sequence of steps is exactly what it does.
I’m using very informal language by saying “how” and “why”. More precisely, my algorithm finds the algorithm that underlies a (natural) process. In an informal sense, that can be thought of as “how” that process works at an abstract layer, while recognizing of course that “how” is an imprecise word that could mean different things to different people depending on their point-of-view.
Since I’m posting, I started testing it this morning on real existing models from different domains and it works shockingly well so far. It is inferring algorithms for auxin transfer in different flowering plant species in under 10 seconds, which is really cool.
I don’t have time to read the whole thread, so this is in part a reminder to myself to do so. But from reading the OP, this sounds somewhat similar to (perhaps the inverse problem of) the work of Markus Hutter with his AIXI-agent, which is theoretically able to infer solutions for arbitrary problems that only exceed the running time of special-purpose algorithms for these problems by a constant factor (IIRC). The problem is that the ‘full’ agent relies on Solomonoff induction, which is based on Kolmogorov complexity, which isn’t computable; so you can only ever instantiate approximations. It seems like (again, on first reading) your algorithm could possibly help either evaluating or generating strategies for something like that.
Another thing that seems vaguely related to me is Schmidhuber’s Gödel machines, which re-write their own code once they have found a proof that the re-write would yield a better strategy.
You have it right. That is the problem, the inductive inference of an algorithm.
You know, I sometimes forget that some of the members of this forum are well informed. I usually have to simplify this, hence the “how” and “why” of an algorithm. If I’m doing my “elevator pitch” and say “inductive inference of an algorithm”, they’re gone. But I say, “We’re trying to take a natural process and determine it’s algorithm, by which we mean, how does that natural process work?” then they get it.
can you be more specific with an example? What are the types of inputs about a natural process into your system? For example, for the one you mentioned above about auxin transfer, what kind of information did you feed into the system that gave it the opportunity to solve the problem?
I decided to persevere, mostly on the basis that I figured you wouldn’t recommend something that was seriously flawed. I’m glad I did. I’ve plowed through more than half of the first lesson set without trouble at all. Work was pretty busy for a couple of days but I think I have time now to do some more learning.
I wish I was! I’m fascinated by the field, but I’m very much just an outside observer coming along for the ride. I love reading about it, though, so I’d appreciate it if you threw more cool stuff our way! Though I suppose I’ll know your work has reached maturity once the killbots come knocking.
My stochastic algorithm inference tool has been accepted at a conference. It is a long running (30+ years) conference, small but of good quality for AI. Very excited!!
Thanks, that was actually helpful. I didn’t read the entire thing or even attempt to understand it all, but I think I was able to get a “feel” for the level of detail and how modeled (e.g. petri-nets etc.).
Usually, a paper will be accepted as a tech demo, poster, oral presentation, with a poster usually being considered better than a demo, and a presentation better than a poster. Although in some cases, a poster in a great conference can be better than a presentation in a lesser conference. In any case, this paper was accepted for an oral presentation, so I will travel to the conference and give a 20 minute talk on the research. The paper is also published in the conference proceedings. The evaluation has already occurred, in that the paper goes through a peer review process before be accepted, but of course anybody listening to the talk may provide some feedback later.
As for pie, well, there is usually a social event, which incorporates something local. So I went to a conference in France recently and we toured one of the palaces. There’s usually a banquet as well. Specifically pie … well, maybe, I will say the conference in France had too many great desserts!