I'm trying to create a game similar to this (Note:When you click 'play', there are SFX in the game which you can't seem to turn off, so you may want to check volume). In particular, I'm interested in knowing how the 'infinite' landscape is generated. Are there any tutorials/articles describing this? I came across procedural generation, but I'm not quite sure what topics I should be looking for (or if it's even procedural generation).
(I'm using C#, but I don't mind the language as I assume the theory behind it remains the same)
That one seems like it would be pretty easy to duplicate -- I would imagine an algorithm that calculates the next "step" of the landscape (the part that is off the screen). It would need to know the prior height (and maybe even the previous slope) in order to then (randomly) increment or decrement the step. You could then tweak the algorithm to be more fluid (gently sloping), or extreme (whipsawing back and forth) as time passes/levels are completed.
Before I clicked the link though, I thought you might have been talking about voxel landscapes -- which I haven't thought about for over a dozen years, but amazed me when I first saw them. I did some googling, and thought you might be interested in this:
http://www.gamedev.net/reference/articles/article655.asp
(Not sure if the Mars demo still exists, or if anyone has a DOS machine to play it on, but this is a good example that shows what it used to look like: http://www.codermind.com/articles/Voxel-terrain-engine-building-the-terrain.html )
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Working on a recent project I wondered how to find a good/perfect path to a target that is moving with a steady speed. I tried standart A* pathfinding but it failed, since the heuristic will be wrong the more the object moves and I just can´t find a way to make that work for me. Maybe you guys got another algorith that should work with just fine or some calculation tuning with A* that would work...
Thanks for your afford :)
A* should in general work, but then of course you need to recalculate every time the target moves. For 99% of cases, this is actually ok. For example, in video games you can get away with only recalculating the best path once every second or so, so it's generally not a huge performance hit.
However, if you really need something more powerful, check out Generalized Adaptive A*, an algorithm specifically designed to handle moving targets. And if you really want to be on the bleeding-edge, there are multiple adaptations of GAA* that are faster in certain cases - see this post (under "moving target points") for more details.
Using A* with a moving target is ok, but you must recalculate the whole path again. I don't think A* likes just having it's destination / goal changed.
Your A* needs to be very well optimised to run in real time and recalculate the new path every time the target moves.
Remember to play with your H to get a balance between working out the shortest path and the quickest to calculate. All depends on your map and obstructions really.
However A* may not be the best path finder for your application, but I'd need to see your map and more info..
I've been looking for a robust method of pathfinding for a platformer based game I'm developing and A* looks like it's the best method available. I noticed there is a demo for the AStar implementation in Godot. However, it is written for a grid/tile based game and I'm having trouble adapting that to a platformer where the Y axis is limited by gravity.
I found a really good answer that describes how A* can be applied to platformers in Unity. My question is... Is it possible to use AStar in Godot to achieve the same thing described in the above answer? Is it possible this could be done better without using the built in AStar framework? What is a really simple example of how it would work (with or without AStar) in GDscript?
Though I have already posted a 100 point bounty (and it has expired), I would still be willing to post another 100 point bounty and award it, pending an answer to this question.
you could repurpose the Navigation2D node for platformer purposes. The picture below shows an example usage. The Navigation2D node makes it possible to navigate the shortest path between two point that lie within the combined navigation polygon (this is the union of all NavigationPolygonInstances).
You can use the get_simple_path method to get a vector2 array that describes the points your agent/character should try to reach (or get close to, by using some predefined margin) in sequence. Place each point in a queue, and move the character towards the different points by moving it horizontally. Whenever your agent's next point in the queue is too high up to reach, then you can make the agent jump.
I hope this makes sense!
The grey/dark-blue rectangles are platforms with collision whereas the green shapes are NavigationPolygonInstance nodes
This approach is by no means perfect. If you were to implement slopes into your game then the agent may jump up the slope instead of ascending it normally. It is also pretty tedious to create all the shapes needed.
A more robust solution would be to have a custom graph system that you could place in the scene and position its vertices. This opens up the possibility to make one-way paths and have certain edges/connections between vertices marked as "jumpable" only. This is a lot more work though if you can not find any such solution online.
I've a friend who wants to learn web programming. He's a physically handicapped person. Actually he uses computer with a trackball and he can press keys one by one and only with one hand. So, I think that his greatest problem will be trying to write special characters that require the use of two hands (such as >,!,#, etc.). First I thought in Visual Studio (Intelissense can be a great help) but does anybody know about tools that can make even easier programming?
I know is an odd question but I'll really appreciate if someone could give me a hand here :)
Thanks in advance
Several companies make programmable keyboards, keypads and footswitches that would make for easy access to those characters normally accessed with the shift key. Some are used as supplements to a standard keyboard, others replace the standard keyboard.
They're designed so you can apply your own labels to the keys according to the functions you assign. Some have software that lets you assign multi-step macros to single keys.
Lots of examples of such products here: http://www.fentek-ind.com/program.htm (just the first page I found with Google)
Another feature worth being aware of is Sticky Keys - on Windows, hit SHIFT 5 times in a row fairly rapidly to turn it on. When Sticky Keys is on, modifier keys like SHIFT, CTRL, and ALT 'stick' until the next key is pressed: so if you want to type the ! character, you can do so by pressing SHIFT and then pressing 1, without having to press both at the same time.
(Note that Sticky Keys turns itself off automatically if you do hold down SHIFT and another key at the same time - but you can turn this feature off so that it stays on all the time via the control panel.)
Not sure how useful speech-to-text will be; it tends to be fine-tuned for English words that you'd find in a dictionary, I'm not sure that it would cope very well with either the heavy use of symbols or the use of non-english text found in most languages (eg printf!).
This answer may seem a bit late, but I hope it will be usefull to many:
A very good program to know, allowing one to input with only 2 movement (be it with a mouse, a joystick, a finger, a toe, the head, eyeballs, etc), and which could allow one to type quite fast once used to it : dasher (wikipedia page), that you can find on : dasher official site
It's surprisingly easy to learn and get into : you "aim" for the next letter, and it grows while going toward your pointer. Once you enter it, on the far side you see the next letters appear, with the most probable ones much bigger than the others (ex: "e" is usually the biggest for the first letter, but once in it, "n" will be quite big as it's a probable next letter. When you have crossed through "ente", "r" will be very big and easy/fast to aim. If you "exit" (by going above or below or by going back) the current letter, it deletes it and therefore you can select another one to replace it. See the wikipedia page for a nice animation showing how it's done.
You can have Dasher use (and train on) specialized dictionnaries to have the most useful letters bigger and therefore easier to "type" (usefull if you intend to do programming, for example. By default the dictionnary is to write letters/mails/etc)
I'm an AI Student, previously I was thinking about something, every time we guys we see a movie, the next time we the movie, it's the same thing, so those who have a knowledge of AI, such as the graph theory and so on, do you think it is feasible to create a dynamic movie, that is the first time you see it, it follows a path in the graph, the next time you see it, it follows a different path and as a result, we get a different movies, do u think this is feasible ??
It's a shame I can't remember the French researcher who's doing research on movie style cameras. While not an interactive movie as you propose, you could alter the strength and importance of each character, and it would position, pan and zoom the camera according to cinematography rules. It looked very promising.
While it would show you the same movie, you could see it in infinitely different variants in regards to camera positioning, each of which could lead to a different interpretation :)
But for your proposal, just go with some logic based planning AI. No need for learning as others says. You have a bunch of sequences, and a bunch of logic to describe how they fit together, which prerequisites they have et cetera. If the logic is good, it would always result in a meaningful film. But it'd be a hard task. It's hard just to make a linear film ;)
(There's a whole chapter in Russel and Norvig)
Where is an Intelligence in it? It looks like a bunch of ifs / switches with random.
The idea of AI is based on learning. Your AI component needs to adjust based on some external inputs, which I can't see in your description.
If the user could somehow tell your AI component that it likes / dislikes what he sees, than it will make sense. For example, you display a slideshow of photographs and the user tells you whether he likes or dislikes a photograph and you then choose future photographs based on his preference. You could learn from other user's preferences, too. That's AI.
CAPTCHAs that ask users to read distorted text are fine for sighted people, but a terrible barrier for those who are blind or have other disabilities. Audio alternatives are occasionally available but still don't help those who are both deaf and blind and can be hard to use with a screenreader (which is already reading words to you).
There exist a couple of solutions that use humans to solve the CAPTCHA on behalf of the user, such as WebVisium and Solona, but these rely on the availability of volunteer operators (for example, Solona apparently has just one volunteer so you have to hope he is awake when you want help).
It occurs to me that the volume of CAPTCHA solutions needed by blind people is very low - I'd guess less than a few hundred per day in a populous country like the UK. This means that unlike the bad folks who want to perform an action many times in a short period, a CAPTCHA assistance service for blind people could afford to devote considerable computational resource - for example, a cloud of computers in Amazon EC2 - to identifying the presented text.
My question is this: assuming you don't care about speed very much, and you have lots of computers available, are there algorithms that let you solve the text-distortion CAPTCHAs that are common today, such as those used by reCaptcha? Or are these problems really intractable even with lots of resource and time?
A few notes:
At this point, my question is just theoretical, but clearly any such service would have to carefully control access to keep spammers out. Perhaps only registered blind people would be allowed to use it.
I am aware that an old Yahoo CAPTCHA was broken a few years ago using an algorithm that runs in seconds on a single computer. I am asking whether modern CAPTCHAs can be broken, perhaps more slowly and with more resource.
I am aware that some new CAPTCHA types are appearing, which ask users to identify kittens or orient a picture. These aren't widespread yet, so I'm just asking about text-distortion for now.
Basically solving a text distortion CAPTCHA consists of three individual steps:
Find out where the interesting parts are
Segment the text into individual letters
Recognize the letters
The only problem that's left which is pretty hard for computers is the second one. The first usually isn't very hard, unless you happen to stumble upon the CAPTCHA from hell. And the third gets solved by computers with a much better success rate than by humans.
An interesting site for learning how CAPTCHAs are broken is the one by the OCR Research Team.
CAPTCHA has been created to avoid machines from detecting the words. It's meant to be read by humans only. Making it more readable for blind/deaf people adds a risk of machines being able to understand them again, thus nullifying their effect.
Spammers did find a very effective way to break the more popular CAPTCHA's though. They just hire cheap labourers to read them, in return for a few cents per working account. As a result, there's a small industry around breaking CAPTCHA's to create millions of accounts that can then be used to send more spam. Compared to the amount gained by the spammers, the costs is almost none. A similar solution could be used by blind/deaf people, who would send the CAPTCHA image to some cheap labourer in China or wherever, where they will reply with the correct words and the blind/deaf person will be able to proceed. Unfortunately, blind people only need this service only a few times while spammers need a continuous flow, thus those labourers will prefer to work for spammers instead. (The pay is better.) Still, the best solution would be to send the CAPTCHA to some friend, let them read and/or decipher it and return the answer.
The ReCAPTCHA style also reads out the words. A simple speech recognition application might be able to recognise whatever is said, although speech recognition still needs more optimizations. Still, you might want to work from that angle, getting the application to listen to the sound byte instead.
When it is possible to break CAPTCHA's, they will just think of better CAPTCHA-like methods. OCR techniques are still improving thus more work will be done to make CAPTCHA's harder. That is, until OCR has become as good as the human eye at recognizing words...
An algorithm could be created, although slow. With 26 lowercase and 26 uppercase letters and 10 digits, it should not be too difficult to come up with an algorithm. With Serif and Sans-serif fonts, the number of combinations would need to be doubled, though. Still, if you try to curve all letters in a similar way as the letter in the CAPTCHA, you should be able to detect a letter which gets covered by the CAPTCHA letter the most. And that would be the most likely candidate. Still needs you to clear lines, dirt and other artefacts from the image that the human eye has less trouble to recognise than a computer. You'd need the following steps:
Clean up the image.
Detect the locations of the letters.
For every letter
3a. Determine the curve of the letter by checking the left side.
3b. Do an overlay of every possible letter/digit to find the one that covers it the best. (That's the most likely letter.)
Once you've found the word, do a dictionary check to make sure it's a real word. (Unless the CAPTCHA doesn't use real words.)
Even though they can twist the letters in the CAPTCHA's, it should be possible to detect the twist rotation that they used simply by looking at the left side of every letter and then trying to apply the same curve to every letter. (52 combinations, plus 10 digits, if digits are also used.) Basically, you'd try to put a box around every letter, then check which letter will contain the least amount of white space. That's the most likely letter.
The main reason why this isn't often used for OCR is basically the need for speed. Step 3a/b tends to be slow, especially if you have to take font style in consideration.
Making this answer bigger but in reply to one of the comments:
There are several ways to cleanup an image. You'd need some color filtering, noise reduction and an algorithm that's able to recognise the noisy lines through an image. The DEFCON slideshow that you've pointed to shows a few simple techniques to filter away some of the noise. It shows that a basic image processing tool can already make an image a lot clearer for a machine to read. A simple blur will clean up random dots and thin lines while color filters would filter away the noisy colours. A next step would be to try to put a box around every letter in the CAPTCHA, hoping the system is able to recognise their locations. I don't know any practical algorithms for this but there should be ways to recognise them. There's software that can create vector images from bitmaps, thus there should be software that's able to calculate a box around a letter.
It is likely that this box won't have rectangular corners, thus you would have to distort all 52 letters to match the same box. Italic or bold shouldn't make much of a difference since these styles are just additional distortions. Serif or Sans-serif does make a difference, though. Serif fonts tend to have a few more spikes and ornaments. Fortunately, there are algorithms that can transform a box to any other figure with four corners.
Regular OCR applications will assume that letters are mostly straight and will just check a few hotspots to find a match. Thus, they sometimes get it wrong because of noise. To crack CAPTCHA, you would need a more sensitive match, preferably "XOR-ing" the CAPTCHA letter image with an image of one of the 52 letters, then counting the number of black and white spots to calculate the ratio. Assuming white=1 and black=0, the result of the XOR should be almost black for the best match.
I think several spammers have already found some useful algorithms to crack CAPTCHA's but for them, keeping these algorithms a secret just keeps them in business.
Another comment, more text. :-)
Segmentation would be a problem, but it's not impossible to solve. It's just extremely complex. But when you've cleaned the image, it should be possible to calculate two lines. One line that touches the bottom of every letter and a second line that touches the top. However, good CAPTCHA's won't put letters on the same lines any more, but those not-so-good ones could be cracked by just following the lines. (Guess? ReCAPTCHA puts letters between two lines!) With two lines, you know the first letter will start at the left, thus you can try overlaying all 52 possibilities there until you've found a match. When you found one, move to the right for the second one. And further until you've read all letters. With two lines to guide you, you don't need a complete box.
Letters tend to use a constant ratio between width and height. With two lines, you can calculate the height of the complete letter and thus get a good estimation of the matching width.
Still, working out the correct algorithm to calculate this all is a bit too much for my poor math skills. You'd need an expert mathematician to crack this algorithm.
My answer to your question "are these problems really intractable even with lots of resource and time?" is to point out that this is the very reason that CAPTCHAs work.
My understanding is that the purpose of a CAPTCHA is to prove that you are human rather than a spam bot. reCAPTCHAs are a novel take on this theme because they take images that represent text that cannot be resolved by OCR (optical character recognition) engines. The difference between a person and a machine in this instance is that specialized algorithm(s) has tried to interpret this image and failed while a "normal" person has the intrinsic ability to interpret the text in a consistently human way. That being said, in the future we hope that someone will come up with better OCR engines so that there needs to be less human intervention in digitizing the worlds information. We hope that someone will come up with an tractable solution to this particular problem.
From your point of view of trying to make CAPTCHAs more accessible to blind people -- who still need to prove that they're people rather than spam bots -- the community needs to become aware of this issue and find a way to identify people in a less vision centric way.
The introduction of CAPTCHA has certainly made the web less accessible to the visually impaired, and I agree with you in citing this as a significant problem that deserves more attention and concern. However, while CAPTCHA can be and has been inconsistently bypassed on popular web sites, I don't think this is a viable long-term solution for those in need. Indeed, the day that the CAPTCHA variants currently present on sites like Facebook, Google, MySpace etc. can be reliably and consistently broken is the day they will become obsolete and abandoned for either stronger variants of the same or an entirely new solution (as you implied, distinguishing cats from dogs in pictures has been a popular alternative trend).
When it comes to online accessibility, what I think those with disabilities need most right now is advocacy. The more people contact software companies, open source groups, and standards bodies and speak out about this need, the more awareness will be raised and that will (hopefully) lead to more action on behalf of the development community. Ultimately, it would be great to see sites like Google or Facebook offering alternative access methods just for their visually impaired users.
Idealism aside, I think it is productive to pursue other avenues like you mentioned with the CAPTCHA volunteer network, possibly even the development of something like OpenID for those with relevant disabilities as a universal form validation pass.
As for the technical aspect of your question, I don't think the availability of additional processing power alone will allow you to reliably and consistently break CAPTCHA. There is A LOT of money in spam, and you can be sure that shady SEO companies and Spammers alike have a great number of servers at their disposal. As Johannes Rössel mentioned, if you want to learn more about how this is done and where the technical difficulty lies, research Optical Character Recognition (OCR) and look at the wide variety of number/letter skewing that occurs on high traffic sites.
This related SO question has a number of good ideas in it, including a DEFCON talk that claims using multiple OCRs and voting breaks many simple CAPTCHAs. This suggests a candidate solution method: distribute the problem over several servers, each of which runs one or more OCR tools in parallel, collect the results, and take the most popular answer. Comments welcome.