Okay here is my problem. I have to implement the Gale-Shapley algorithm for the alignment of two ontologies. I read the first 200 pages of the book "Ontology Matching" by Jerome Euzenat and Pavel Shvaiko and now I understand some of the basics of ontology matching but the problem is that the more I read the more confused I become. I really think that the problem is relatively easy but I really can't get around it and I am not getting clear instructions from my professor as they insist that I should decide everything on my own. The problem is that I don't understand the whole process. I understand the Stable Marriage Problem, I understand the basics of ontology matching but I can't seem to "connect" everything. If somebody could explain to me how the whole thing should look and how to start (the basics of a Design Document) I will be incredibly grateful.
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I'm brand new here, and also to Lua, so please bear with me...
I'm building an Airport in Minecraft, with my kids. I'm an overachiever and a dreamer, and at some point, my brain decided it would be a FANTASTIC idea to add in a cosmetic element that I have absolutely NO idea how to do. Smart, right?!
See, I got it in my head that I want to have display screens in our Airport that show the flight information of incoming/outgoing flights. Fast forward to my discovery of the Opencomputers mod for Minecraft, a few hours of watching tutorials on how to operate it, and thus began my search for knowledge of that which is the Lua language. Fortunately, I have a wee bit of coding experience (thanks to my college days) and I picked up the very basic of the basics. (It seems similar to C.) I've gleaned just enough to accomplish the bigger part of my goal: I've managed to write the bare bones of the program I dreamed up, and it works...for the most part. (I still need to figure out some redundancies and such...all in good time.)
But...it's so very plain, and not fancy at all. It doesn't look even remotely like what I was picturing in my head, and this simply will not do. So now I am on a quest to discover how to format the output of my program and make it look fantastic...or at least, as close as I can get it to what was in my head. I have managed to figure out how to change the gpu screen colors (foreground, background) so that is why it's blue/white. But it's not quite what I wanted, and it resets if the system is turned off. My goal is to change the format of the program output itself, not just the Opencomputers screen block. I've googled this until I'm blue in the face, and I have pored over forums and code tutorials and the like...only to fail at finding the information I need. It's possible that I've passed up the answer, simply because I'm still very new to the language, but that's another good reason for me to be here, right?
And so, I turn to you, O Great Dwellers of the Interwebs, the Keepers of Vast Programming Knowledge, for assistance. Please, pretty please, help me make my program look awesome. My kids just may think I'm the coolest Mom on the planet, and that would be more than fantastic...Not to mention we'd have one kickass airport to play around in. :)
Here's what you'll probably want to know:
First, This pic is what I want, (on the left) and what I have (on the right).
And here is the code for my program: http://pastebin.com/60nPfpB8
I apologize up front for all of the noob mistakes that my code is more than likely riddled with. I haven't figured out yet how to make the functions repeat themselves, or a good way to utilize a 24 hour clock for the "time" function. So any suggestions there would be welcome as well.
Thank you for taking the time to read, and I appreciate any help I can get with this. :)
I have been trying to implement jump-point search to my already implemented A* pathfinding code, but I don't fully understand how it works. The website here (which is all that I could find on it) doesn't really explain much about how to prune or how to determine a jump-point successor. Could anyone explain these two things in detail?
The technical details are in the research paper, which can be found on Alban Grastien's web page.
There is also a tutorial on aigamedev.com.
It appears that an improved paper will appear at ICAPS 2014, but I don't believe the papers are online yet.
If these resources are insufficient, a more directed question (what don't you understand) will be easier to answer. But, one thing important to note is that JPS scans the state space looking for obstacles. In doing so it may look at far more states than A* does. But, its time savings come from not putting most states in the OPEN list.
In addition to the original 2011 paper, I also found this site: https://zerowidth.com/2013/a-visual-explanation-of-jump-point-search.html particularly helpful, as it explains how JPS works in simple terms with diagrams, and also includes a grid where you can add/remove obstacles and visualize how JPS finds and expands jump points.
I'm thinking about writing a program that asks the user to think of an object(a physical one) and then it asks questions about the object and tries to figure out what the user was thinking. (Similar to http://20q.net)
I tried to do it in Python but figured my approach was naive and would be very inefficient. How would you guys do this?
Doing this efficiently requires a somewhat advanced method in probability called Kullback-Liebler Divergence. Applied to decision trees (which is what you want to do) it is often called Information Gain.
But don't let that stop you! Do some searches for implementation samples of decision trees and start from there. I'd write a much simpler program before you go about solving 20 Questions.
Also, take a look at http://www.20q.net/ . Click "Think in English" then "Classic 20Q". It's scary good, sometimes.
Sounds like you want to make a computerized 21 questions game. I'd do it with a tree of questions and answers.
Here is a nice stackoverflow article about implementing trees in python
How can I implement a tree in Python? Are there any built in data structures in Python like in Java?
I've been studying hierachial reinforcement learning problems, and while a lot of papers propose interesting ways for learning a policy, they all seem to assume they know in advance a graph structure describing the actions in the domain. For example, The MAXQ Method for Hierarchial Reinforcement Learning by Dietterich describes a complex graph of actions and sub-tasks for a simple Taxi domain, but not how this graph was discovered. How would you learn the hierarchy of this graph, and not just the policy?
In Dietterich's MAXQ, the graph is constructed manually. It's considered to be a task for the system designer, in the same way that coming up with a representation space and reward functions are.
Depending on what you're trying to achieve, you might want to automatically decompose the state space, learn relevant features, or transfer experience from simple tasks to more complex ones.
I'd suggest you just start reading papers that refer to the MAXQ one you linked to. Without knowing what exactly what you want to achieve, I can't be very prescriptive (and I'm not really on top of all the current RL research), but you might find relevant ideas in the work of Luo, Bell & McCollum or the papers by Madden & Howley.
This paper describes one approach that is a good starting point:
N. Mehta, S. Ray, P. Tadepalli, and T. Dietterich. Automatic Discovery and Transfer of MAXQ Hierarchies. In International Conference on Machine Learning, 2008.
http://web.engr.oregonstate.edu/~mehtane/papers/hi-mat.pdf
Say there is this agent out there moving about doing things. You don't know its internal goals (task graph). How do you infer its goals?
In way way, this is impossible. Just as it is impossible for me to know what goal you had mind when you put that box down: maybe you were tired, maybe you saw a killer bee, maybe you had to pee....
You are trying to model an agent's internal goal structure. In order to do that you need some sort of guidance as to what are the set of possible goals and how these are represented by actions. In the research literature this problem has been studied under the terms "plan recognition" and also with the use of POMDP (partially observable markov decision process), but both of these techniques assume you do know something about the other agent's goals.
If you don't know anything about its goals, all you can do is either infer one of the above models (This is what we humans do. I assume others have the same goals I do. I never think, "Oh, he dropped his laptop, he must be ready to lay an egg" cse, he's a human.) or model it as a black box: a simple state-to-actions function then add internal states as needed (hmmmm, someone must have written a paper on this, but I don't know who).
I would like to know if there are any tools that can help me model C applications i.e. Functional programming.
E.g. I'm currently building a shared library.
But to communicate my design visually, I need something like UML. I would like to do this so that the person reviewing my design need not read through 100s of pages of functions, variables and so on.
I have read about UML for C, which I'm considering.
If there is anything better out there, please let me know.
The bottom line is to visualize the design of C applications and modules without reading through 100s of pages of text, because it takes time and is difficult for the reviewers.
Any help in this area from the experts here would be much appreciated.
Thanks.
A well written text documentation brings you a far. Much further than any UML diagram could ever achieve.
You should split this in two parts:
What do you want to say?
What's the best way to saying it?
Whatever formalism you use to answer the second part, you should be sure it's not ambigous.
The good of UML is that a lot of semantic is already defined by the language so you don't have to include a definition of what those boxes, lines and arrows mean in a collaboration diagram.
But most importantly, documenting something means create a path for others to understand the subject you are documenting. A very precise description that offers no clue on how to read it is as good as none. So, use UML, Finite state machines, ER diagrams, plain English, whatever you want but be sure to include a logical path that your "readers" can follow to understand what's going on.
I had a friend that was a fan of "preciseness at all cost" and it would ask us to go through all the details before some sort of meaning would emerge.
I once ask him to do this experiment: on his next trip to an unknown city, he would have to carry the most precise map he could get. Much better, he would have to carry a 1:1 map of the city with every single detail exactly reported in scale. That way he couldn't get lost!
He declined but I would love to see him trying to use that map. Just even folding it! :)
Whatever you like. It's not a standard but many devs use it and understand it. If it does help you to communicate with other people and document your work -> its for you. If it just takes too much time and you think it's not effective, drop it. Also, don't bother with all details, as long as it resembles UML and your team can work with it, it's fine.
It's meant to help you, not waste you time.