In a project I'll be working on soon there will be a need to generate avatars. The generation process will be one of those where the user can select different heads, hairstyles, clothing, etc. Some items will also be unavailable at first and will have to be earned or purchased.
I already have a fair idea on how to do this, but since it is a nontrivial amount of code, it would be nice to see working examples of code. Ideally I could just take a script and integrate into my page, but just gathering ideas from other people would be good too.
I'll be working with PHP, but examples in other languages are welcome too.
Added: To clarify, I don't mean a random avatar generator (or one that generates an avatar based on some hash value). A random avatar generator is subtly different from what I have intented. In a random avatar generator the programmer-artist has a much greater say of what goes where. He can carefully pick out pieces that will not conflict with each other, and he can discard those that give him trouble.
In my case the avatar generator is more like this. The user chooses which head to use, which hairstyle to apply, which piece of clothing to use, etc. There are way more pieces there, with artists adding new ones every once in a while. It's much harder to test how pieces will or won't fit together. Sometimes more advanced blending is required (like a hat would have a part of it in front of hair, and part of it behind the hair). Etc.
[EDIT: Revised answer to updated question]
I think that it's primarily a matter of designing the parts accordingly. You have some basic forms (male, female, tall / small, etc.) for which you have stylesets (e.g. hair) designed to match and align perfectly. Solving this algorithmically instead is probably a bad choice in terms of workload and probably not necessary for non-animated figures.
However, maybe you'll need some additional alpha-channel/transparency masks or something for combining head, hair and hat.
Other than that, these parts would have to be combined layer for layer like Monster ID.
infernowebmedia.com
They sell a cheap and fully functional website code to make your own avatar site.
Related
I'd like to write an application, which would imitate a player in an online game.
About the game: it is a strategy, where you can:
train your army (you have to have enough resources, then click on a unit, click train)
build buildings (mines, armories, houses,...)
attack enemies (select a unit, select an enemy, click attack)
transport resources between buildings
make researches (economics, military, technologic,...)
This is a simplified list and is just an example. Main thing is, that you have to do a lot of clicking, if you want to advance...
I allready have the 'navigational' part of the application (I used Watin library - http://watin.sourceforge.net/). That means, that I can use high level objects and manipulate them, for example:
Soldiers soldiers = Navigator.GetAllSoldiers();
soldiers.Move(someLocation);
Now I'd like to take the next step - write a kind of AI, which would simulate my gaming style. For this I have two ideas (and I don't like either of them):
login to the game and then follow a bunch of if statements in a loop (check if someone is attacking me, check if I can build something, check if I can attack somebody, loop)
design a kind of scripting language and write a compiler for it. This way I could write simple scripts and run them (Login(); CheckForAnAttack(); BuildSomething(); ...)
Any other ideas?
PS: some might take this as cheating and it probably is, but I look on this as a learning project and it will never be published or reselled.
A bunch of if statements is the best option if the strategy is not too complicated. However, this solution does not scale very well.
Making a scripting language (or, domain specific language as one would call that nowadays) does not buy you much. You are not going to have other people create AI agents are you? You can better use your programming language for that.
If the strategy gets more involved, you may want to look at Bayesian Belief Networks or Decision Graphs. These are good at looking for the best action in an uncertain environment in a structured and explicit way. If you google on these terms you'll find plenty of information and libraries to use.
Sounds like you want a finite state machine. I've used them to various degrees of success in coding bots. Depending on the game you're botting you could be better off coding an AI that learns, but it sounds like yours is simple enough not to need that complexity.
Don't make a new language, just make a library of functions you can call from your state machine.
Most strategy game AIs use a "hierarchical" approach, much in the same way you've already described: define relatively separate domains of action (i.e. deciding what to research is mostly independent from pathfinding), and then create an AI layer to handle just that domain. Then have a "top-level" AI layer that directs the intermediate layers to perform tasks.
How each of those intermediate layers work (and how your "general" layer works) can each determined separately. You might come up with something rather rigid and straightforward for the "What To Research" layer (based on your preferences), but you may need a more complicated approach for the "General" layer (which is likely directing and responding to inputs of the other layers).
Do you have the sourcecode behind the game? If not, it's going to be kind of hard tracing the positions of each CPU you're (your computer in your case) is battling against. You'll have to develop some sort of plugin that can do it because from the sound of it, you're dealing with some sort of RTS of some sort; That requires the evaluation of a lot of different position scenarios between a lot of different CPUs.
If you want to simulate your movements, you could trace your mouse using some WinAPI quite easily. You can also record your screen as you play (which probably won't help much, but might be of assistance if you're determined enough.).
To be brutally honest, what you're trying to do is damn near impossible for the type of game you're playing with. You didn't seem to think this through yet. Programming is a useful skill, but it's not magic.
Check out some stuff (if you can find any) on MIT Battlecode. It might be up your alley in terms of programming for this sort of thing.
First of all I must point out that this project(which only serves educational purposes), is too large for a single person to complete within a reasonable amount of time. But if you want the AI to imitate your personal playing style, another alternative that comes to mind are neural networks: You play the game a lot(really a lot) and record all moves you make and feed that data to such a network, and if all goes well, the AI should play roughly the same as you do. But I'm afraid this is just a third idea you won't like, because it would take a tremendeous amount of time to get it perfect.
I have a course in my current semester in which I'm required to do a project on application of AI. I have decided to do this on game AI. I have 2 basic ideas: implementing an FPS bot(s) or implementing soccer AI.
I'm quiet a noob at AI right now, I've implemented basic pathfinding algos (A*, etc), and have studied about Finite state machines, some First Order logic, basic Neural Network stuff(Backpropagation ALgo), and am currently doing a course on Genetic Algorithms.
Our main focus is on the bot right now. Our plans include:
Each 'bot' would be implemented using a Finite State Machine (FSM), which would contain the possible states the bot could have; & the rules for the action/state changes that are going to take place when it receives an input.
In bot group movement, each bot would decide whether to strike, ways to strike; based on range, number of bots, existing fights using Neural Networks.
By using genetic algorithms the opponents next move could be anticipated based on repetitive moves.
Although I've programmed a few 2d games till now in my free time (like pacman, tetris, etc), I've never really gone into the 3d area. We will most probably be using a 3d engine.
We want to concentrate most of our energy on the AI part. We would like not to be bothered with unnecessary details about the animation/3d models, etc. For example, if we could find a framework which has functions like Moveright() which just moves the bot to the right, it would be really awesome.
My basic question is : is it too ambitious to go about it in the way we have planned, considering the duration of the project is abour 3 months? Should we go 3d and use a 3d game engine? is it easy to use such engines, if you have no experience with them before? If yes, what kind of engine would be suitable to our project?
I came accross another idea, given in the book AI Game programming by example, where the player would have a top down view of the bots. Would that way be more appropriate?
Thanks .. sorry about the length of the question .. it's just that my problem is a bit too specific.
My basic question is : is it too
ambitious to go about it in the way we
have planned, considering the duration
of the project is abour 3 months?
Yes -- but that's not necessarily a bad thing :)
Should we go 3d and use a 3d game
engine?
No. Mainly because you said:
We want to concentrate most of our
energy on the AI part.
Here's what I'd do, based on my experience (and knowing that, as a student, I often bit off way more than I could chew, too):
Make your simulation function irrespective of a graphical component. Have it publish "updates" to another layer, that consist of player and ball vectors. By doing so you'll be keeping your AI tasks separate from everything else, which means you have fewer bugs to worry about, and you can also unit test your underlying simulation much easier.
Take those "updates" and create your first "visualization" layer -- make it the simplest 2D representation possible. It could just be a stream of text lines: "Player 1 has the ball / Player 1 kicked ball at (30,40) with speed 20kph". That will be hard enough for your first pass since you'll be figuring out how to take data published by the simulation and doing something with it.
Your next visualization might add a 2D grid of ANSI graphics (think rogue-like) to actually show players and the ball moving. Your next one after that might be sprites. And so on. Note how you incrementally increase the complexity of your visualization... don't make your first step go to using a technology (3d graphics engine) you've never used before. (You'll never finish your project in that case.)
As for your questions about which route to take -- FSMs, NNs, GAs, top-down design -- you should rank your interest in them from most to least (along with the rest of your group) and then tackle them, in that order. You might consider doing one style for one team and a different design for the other team. You might want to make your FSM team play against a FSM team that's had an additional tweak done to it, in order to compare and contrast if you think your changes are actually being beneficial (you might be surprised and find out they make the team worse). Actually, that's where unit testing and splitting the simulation from the visualization come in very, very handy -- you should be able to "sim" as many games as you need to to get experimental results without worrying about graphics. You might even do it in batches overnight with scripts.
In general, my advice to you is this: break down your project into the tiniest pieces you can, and tackle them one at a time, so no matter where you're at when time runs out, you'll have something interesting to show off.
You could have a look at guntactyx, that's what I had to use when I did my AI unit at uni.
It takes care of all the display, physics, sound etc... for you, all you have to do is program your team of bots.
The API includes functions to make the bot move left or right, shoot, hear sounds (like gun shots) etc... and it comes with a few sample bots so you don't start from scratch.
Also, it's quite fun to watch your bots battling your friends' bots :)
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[Objective-C]
Do you still use Styrofoam balls to model your systems, where each ball
represents a class?
Tom Love: We do, actually. We've also done a 3D animation version of
it, which we found to be nowhere near
as useful as the Styrofoam balls.
There's something about a physical,
conspicuous structure hanging from the
ceiling right in the middle of a
development project that's regularly
updated to provide not only the
structure of the system that you're
building, but also the current status
of each one of the classes.
We've done it on 19 projects the last time I've counted. One of them was 1,856 classes, which is big - actually, probably bigger than it should be. It was a big commercial project, so it needed to be somewhat big.
Masterminds of Programming
It is the first time I've read or heard about using styrofoam balls to model classes.
Is that a commonly used technique? And, how does that sort of modeling help us to design better the system?
If you have any photos to share which can show us how the classes are represented it'd be great!
Update: So, it seems that the material most people use is the paper. Styrofoam balls are actually oddballs, not a commonly used technique.
Noticeable techniques:
"paper plates and string" modeling, NealB
Post-it Notes on a whiteboard, Jason
Class-Responsibility-Collaboration cards, duffymo
Sheets of ruled paper taped to the wall, AMissico
Thank you all for the very good answers.
I found a couple of styrofoam models for:
Windows 95
and
Lotus Notes
(if that helps)
Actually, here's a Tom Love case study that shows a couple of his models.
This model may represent the least
expensive CASE tool on the market --
materials cost $20.35. It was more
useful than any CASE tools I have ever
used.
We used it in three important ways.
It fixed the number of classes that we would deliver in the finished
application and we did not allow new
ones to be added, unless existing ones
could be removed.
It was a very useful way to publicly document which classes had
been code reviewed (blue ribbons) and
tested (green ribbons).
It helped everyone understand what was being built and how much time and
effort it takes to do testing,
documentation and code reviews.
Edit: photo of object model
alt text http://img686.imageshack.us/img686/82/stryrofoamobjectmodel.jpg
The styrofoam ball model appears to date back to the mid 1990's - a time when CASE (Computer Aided Systems Analysis)
systems were all the rage.
At that time CASE systems promised significant benefits but were dismally slow,
buggy, unstable, overextended and downright awkward to use. Basically, long on potential but short on delivery.
I remember having a conversation with an analyst working on a different project from mine. Her team had
become so frustrated with their CASE system that they trashed it and resorted to "paper plates and string"
modeling. They reserved a meeting room, removed all the furniture, and laid out their process model using labeled
paper plates with strings (representing data flows) connecting them. She claimed it was much more
useful than the CASE system it replaced.
I suspect that the styrofoam ball model had similar roots.
Using styrofoam balls or paper plates fostered design "buy-in". If a team
finds something to rally around it naturally creates a common design focus. It is simple, concrete and
minimal - using it requires a lot
of face to face interaction and discussion. And that is where the value comes from. I suspect
if you brought a new person into the project and told them to bring themselves up-to-speed by
reviewing the "model" they would be "dead in the water". However, walk them through the
"model" and a real conversation would occur where all the required information need to
perform on the project would be imparted very quickly and efficiently.
Do I think styrofoam balls could become a sustainable modeling tool? No, I don't. They would be a real
pain to keep up to date in a changing environment. They convey little information. There are better tools available
today. And most importantly, if the team you are working with don't "buy" it, and they
probably won't, it will look really stupid - kind of like a sports team mascot, a rallying point
only if the team "buys it".
No, we don't do this. And in my 30-odd year history in the IT industry, I've never heard of anyone doing this.
The only way this could help you design better systems is by:
keeping the class count down since it's hard to build the styrofoam model; and
minimising changes, since updating it would be a serious pain in the rear end.
Other than those two dubious features, I can't see this as being very useful. I'd almost conclude it was some sort of prank. Far better to do some real work, I think.
Seriously, if we tried to model our application with styro coffee cups and straws, our bosses would be calling the men in white coats.
Post-it Notes on a whiteboard seem to be popular in the circles I travel in. Objects go on the Post-Its, and you rearrange them until you get your relationships the way you want em.
And then there are the Color Modeling people who use a 4-pack of colored Post-Its and assign an archetype to each color. It doesn't sound like this is much of an improvement, but standing across a room looking at it, you can tell where there are missing features or unidentified objects in the system.
There is one application to this that I think we tend to forget-- using tools to articulate an architecture comes naturally to us after years in the industry, but there are valuable, albeit less technically-minded, stakeholders who may not grasp vital concepts as readily. It would sometimes be a lifesaver to point to a cluster of balls and say, "This is the Language Processing Model, and if I implement the feature you want, it will have consequences here, here, and here. You can see that there are a lot of balls connected there".
Architects, be they designing buildings or systems, might rely on those tangible models to indoctrinate the check writers into the process.
And I thought that UML was useless. The styrofoam ball model makes UML look positively elegant by comparison.
Ward Cunningham's CRC card idea is more useful, even cheaper, and still retains that tactile quality that Dr. Love was after.
I had never heard of the idea until I read this question. It deserves an up vote for originality. And the "Windows" and "Lotus Notes" pictures are priceless.
Sheets of ruled paper taped to the wall, where each sheet is a component, class, entity, or whatever is needed. Everyone has a pencil.
Everyone can write on them "flushing" out the model during the design meetings. Such as, meeting notes, implemetation notes, new classes, removed classes, reasons why you do not have a particular class, and so on. After the design meeting, the principal designer takes them down and rewrite them, again "flushing" them out with pen in "rough-draft" versions. The designer can then make decisions based on the notes of each sheet, create new sheets for any additional components. Generate topics for next meeting, note any descrepancies, note any design / implementation details needed for coding, or whatever else they need to do.
Repeat the meetings until everyone is satisfied. Pencil is new stuff, pen is previous items. Once everyone is happy, the designer creates the working-draft, and posts where everyone can see and initial, in pen, their acceptance of the "working-draft".
Nothing is final. Pen versions are "latest" versions. Pencil versions are "work-in-progress" or "draft" versions.
Simple, fast, flexible, no wasting time on the computer, with high visiblity. Working man's Wiki.
No. My team does not do this.
And I am badly tempted to mock with image macros. But I'm contemplating that the idea is silly enough that it is self-mocking.
I've got a WinForms client-server app that displays various offers in a list. Every user (client) has a "rating". An offer consists of various data including a minimum and maximum rating. If a user's rating does not fall in that interval, he should not be able to take the offer.
Of course I could just perform some server filtering and send a list of offers prefiltered for each user to the client application. But that would surely, and rightfully, lead to confused requests "Why isn't this offer showing up? I know it exists, it shows up on [other user]'s screen."
How should I handle this? My favorite solution so far is to grey out the offer and add a tooltip "You can't take this offer because your rating is too high/low" while displaying greyed-out offers at the bottom of the list to leave the actually valid offers easily visible on top of the list.
A disabled option tells the user:
The action is possible.
Just not right now.
But the user can make it possible.
Unless there is some simple action the user can do to change his or her rating (e.g., by selecting some other controls in the same window), do not use disabling and do not show the offers. Disabling may confuse some users who will then hunt around the window for something to do to enable those offers. It’s a great idea to use a tooltip to explain disabled objects, but that’s not a standard and not all users will think to hover the mouse over a disabled option (Why should they? It’s disabled).
Including offers users can’t have, even when disabled, clutters your display, forces more scrolling, and distracts the users from the offers you actually want them to consider. Furthermore, showing unavailable offers can come across as taunting (“ha, ha, your rating isn’t high enough”) and may diminished the perceived value of the available offers by comparison, resulting in lower user satisfaction.
It seems unlikely to me that users are going to go around comparing the offers on their windows, but maybe you have user research saying they do. In any case, you should label the list of offers to make the criteria clear (e.g., “Offers available at your rating” may be sufficient).
If you want to encourage users to increase their ratings, then maybe include something advertising the benefits of an improved rating. For example you could have a link "-Improve your rating- by four points and get -five additional offers-." The first -link- tells users how to improve their rating, while the second lists the offers as a motivator. The latter link should only be there if the offers will still be available if the user actually succeeds in getting four more points.
That sounds like a good way to do it.
As a slight improvement, if it makes sense for your application, you might consider including the actual numbers in the tooltip, e.g.:
This offer requires a rating between 5 and 8. Your rating is 4.
A friend of mine is beginning to build a NetHack bot (a bot that plays the Roguelike game: NetHack). There is a very good working bot for the similar game Angband, but it works partially because of the ease in going back to the town and always being able to scum low levels to gain items.
In NetHack, the problem is much more difficult, because the game rewards ballsy experimentation and is built basically as 1,000 edge cases.
Recently I suggested using some kind of naive bayesian analysis, in very much the same way spam is created.
Basically the bot would at first build a corpus, by trying every possible action with every item or creature it finds and storing that information with, for instance, how close to a death, injury of negative effect it was. Over time it seems like you could generate a reasonably playable model.
Can anyone point us in the right direction of what a good start would be? Am I barking up the wrong tree or misunderstanding the idea of bayesian analysis?
Edit: My friend put up a github repo of his NetHack patch that allows python bindings. It's still in a pretty primitive state but if anyone's interested...
Although Bayesian analysis encompasses much more, the Naive Bayes algorithm well known from spam filters is based on one very fundamental assumption: all variables are essentially independent of each other. So for instance, in spam filtering each word is usually treated as a variable so this means assuming that if the email contains the word 'viagra', that knowledge does affect the probability that it will also contain the word 'medicine' (or 'foo' or 'spam' or anything else). The interesting thing is that this assumption is quite obviously false when it comes to natural language but still manages to produce reasonable results.
Now one way people sometimes get around the independence assumption is to define variables that are technically combinations of things (like searching for the token 'buy viagra'). That can work if you know specific cases to look for but in general, in a game environment, it means that you can't generally remember anything. So each time you have to move, perform an action, etc, its completely independent of anything else you've done so far. I would say for even the simplest games, this is a very inefficient way to go about learning the game.
I would suggest looking into using q-learning instead. Most of the examples you'll find are usually just simple games anyway (like learning to navigate a map while avoiding walls, traps, monsters, etc). Reinforcement learning is a type of online unsupervised learning that does really well in situations that can be modeled as an agent interacting with an environment, like a game (or robots). It does this trying to figure out what the optimal action is at each state in the environment (where each state can include as many variables as needed, much more than just 'where am i'). The trick then is maintain just enough state that helps the bot make good decisions without having a distinct point in your state 'space' for every possible combination of previous actions.
To put that in more concrete terms, if you were to build a chess bot you would probably have trouble if you tried to create a decision policy that made decisions based on all previous moves since the set of all possible combinations of chess moves grows really quickly. Even a simpler model of where every piece is on the board is still a very large state space so you have to find a way to simplify what you keep track of. But notice that you do get to keep track of some state so that your bot doesn't just keep trying to make a left term into a wall over and over again.
The wikipedia article is pretty jargon heavy but this tutorial does a much better job translating the concepts into real world examples.
The one catch is that you do need to be able to define rewards to provide as the positive 'reinforcement'. That is you need to be able to define the states that the bot is trying to get to, otherwise it will just continue forever.
There is precedent: the monstrous rog-o-matic program succeeded in playing rogue and even returned with the amulet of Yendor a few times. Unfortunately, rogue was only released an a binary, not source, so it has died (unless you can set up a 4.3BSD system on a MicroVAX), leaving rog-o-matic unable to play any of the clones. It just hangs cos they're not close enough emulations.
However, rog-o-matic is, I think, my favourite program of all time, not only because of what it achieved but because of the readability of the code and the comprehensible intelligence of its algorithms. It used "genetic inheritance": a new player would inherit a combination of preferences from a previous pair of successful players, with some random offset, then be pitted against the machine. More successful preferences would migrate up in the gene pool and less successful ones down.
The source can be hard to find these days, but searching "rogomatic" will set you on the path.
I doubt bayesian analysis will get you far because most of NetHack is highly contextual. There are very few actions which are always a bad idea; most are also life-savers in the "right" situation (an extreme example is eating a cockatrice: that's bad, unless you are starving and currently polymorphed into a stone-resistant monster, in which case eating the cockatrice is the right thing to do). Some of those "almost bad" actions are required to win the game (e.g. coming up the stairs on level 1, or deliberately falling in traps to reach Gehennom).
What you could try would be trying to do it at the "meta" level. Design the bot as choosing randomly among a variety of "elementary behaviors". Then try to measure how these bots fare. Then extract the combinations of behaviors which seem to promote survival; bayesian analysis could do that among a wide corpus of games along with their "success level". For instance, if there are behaviors "pick up daggers" and "avoid engaging monsters in melee", I would assume that analysis would show that those two behaviors fit well together: bots which pick daggers up without using them, and bots which try to throw missiles at monsters without gathering such missiles, will probably fare worse.
This somehow mimics what learning gamers often ask for in rec.games.roguelike.nethack. Most questions are similar to: "should I drink unknown potions to identify them ?" or "what level should be my character before going that deep in the dungeon ?". Answers to those questions heavily depend on what else the player is doing, and there is no good absolute answer.
A difficult point here is how to measure the success at survival. If you simply try to maximize the time spent before dying, then you will favor bots which never leave the first levels; those may live long but will never win the game. If you measure success by how deep the character goes before dying then the best bots will be archeologists (who start with a pick-axe) in a digging frenzy.
Apparently there are a good number of Nethack bots out there. Check out this listing:
In nethack unknown actions usually have a boolean effect -- either you gain or you loose. Bayesian networks base around "fuzzy logic" values -- an action may give a gain with a given probability. Hence, you don't need a bayesian network, just a list of "discovered effects" and wether they are good or bad.
No need to eat the Cockatrice again, is there?
All in all it depends how much "knowledge" you want to give the bot as starters. Do you want him to learn everything "the hard way", or will you feed him spoilers 'till he's stuffed?