AI and Gaming

Hi,
I took M's advice and found some tutorials. I created to projects on one PC...added text boxes and connect/send buttons. I got it to work. Even added text to speak control and one line of code so we could send 'spoken' messages to each application. Geeky for sure. ;-)

I kept getting some inpredicatable errors, especially if I 'reconnected' during a session...stuff like that. I couldn't find any solid examples with bulletproof errorhandling for two Apps on same PC. I'll look for that when I have some free time.

I will keep this interface method between 2 Apps in mind as I grind away at the new AIP version.

Regarding AIP 0.4v, I am rewriting most of the code because I have since come up with better ways of dealing with things. I am allowing for 15x15 grid, with larger cells and fonts. I have global variables that allow for 2 types of checkerboard patterns, random patterns where teacher selects cells to be out of play (crossword puzzle looking pattern) and a few other whistles. Now this all works...pretty cool looking.

At www.clg-net.com/ai/aipsl.htm I am composing a scripting language specification for use with v0.4. It is a work in progress but represents the new language...increasing AIP keywords from about 20 to 80...big jump but necessary for AIP to learn chess.

On paper, it is a simple matter to write AIP to play TTT or chess...that is, it plays legally. However, I must spend time coming up with a novel scheme for AIP to take chess lessons and convert them into some principles to guide later play. I have constructed some Excel sheets with checkerboards and 64 bit table to play with '1's and '0's. Perhaps I can get this. Thought getting AIP to learn to play legal chess is my core objective...the rest comes later.

Now, regarding a program that can modify itself...wait for v0.5. ;-) Yeah right!

Actually, the Engine must include hundreds of functions that are hardcoded that deal with numbers, strings, 2D, 3D, etc. From this the program must allow the user to define new keywords, their variable types and functions that they can connect to...or allow for the writing of macros by the program itself...based upon core language set. The Engine would be .EXE/.DLL but the added modification of program would be perhaps ASCII file formatted.

Maybe we can construct a simple program experiment where we define some AI, a goal, some key functions, program self-macro creation ability and see what happens? An example would be to write a program that can add and subtract. Give it ability to write macros...give it comprehension of summing. See if it can learn on its own to create a multiplication macro function on its own...and then use this to discover division, averages, etc.

I think that would be a decent experimental concept. What do you think?

Regards,
ChuckB

Sounds good Chuck. Winsock is pretty easy once you get the basics down (ive done a simple web server, and telnet server before).

Like I said, the self modifying AI sounds like fun, and I think it is doable. I would love to work on something like that with you. The summation and subtraction AI should certainly be feasable, and would be a great proof of concept.

Z.

I've been reading through this thread, and the ideas shown here are genius! Chuck, AIP works marvelously! After about 5 games AIP was winning and tieing every time! This is fabulous! :cool: :cool: :cool: :cool: :cool: :cool: :cool: :cool: :cool: keep it up!

Thanks Steve. I appreciate the feedback. If you can give this a try... Start the program that has been trained by you. Start a second program that has not been trained. You will need to serve as the interface between the two programs. Now, play them against the other.

Theoretically, the second program should learn after a few games. At which time, there comes a learning plateau where the program kind of hits a 'mental block'. :-)

What should happen, but doesn't, is the AI program should do something novel...unexpected...creative...such that it invents a new strategy all by itself...and continues to kick tail.

Of course, this is really limited with TicTacToe. However, I believe this should be the expected behavior of AIP playing a chess game or something in which game strategy can be developed.

Well, if you can do the experiment above, give it a shot and report back to this thread your findings.

Thanks again,
ChuckB

Hi Z,
I am going to build AIP v0.4 to be able to learn legal checkers/chess and larger pattern matching games...with minimal input on further reasoning and creating additional strategies. This will satisfy my requirements for a program that can be taught a significant variety of games.

I will be spending the next few weeks with a pad of paper while sitting with family in evening, attending meetings, sitting at desk between classes,etc...actually working on some model for AIP developing and refining its knowledge base...I am seeing tiny grid cells and bits in my mind as I close my eyes. :-) Maybe I can develop a function(s) that will allow AIP to play better and better rather then just legally. Again, I must avoid any hardcoding of program to play chess...just give it the ability.

I would like to work on the self-modifying AI. It will take a lot of work up front developing a model in concept, specifying goals and the test for success, etc. Of course, this would probably be many weeks/months in the running. I must devote a lot of evenings to developing an instructional video with my PC and that will eat into my time...and AIP v0.4.

So, if you want to start slowly on this project I am up to it. Let me know if the timetable is okay for you.

We can develop Word docs describing our ideas and plans, or use this forum thread or I can setup a web folder and give you FTP access so we can post our ideas, sample code, etc.

Regards,
ChuckB

The idea of making program develope its own strategies can only be done by allowing the strategies to be developed. Giving the program a rather complex state doesn't boost its capabilities, it boosts its uses, often including faulty uses. The artificial intelligence itself can never be improved, its a turingmachine.

But, for those who don't know, it always looks impressive, there's just no magic involved..

I think functional/logical languages like prolog or haskell is rather suited for what you are doing.

Kedaman is sort of right - but I think his expectations are a little high ;) . Chuck's AIPs are never going to 'learn' anything outside their ability to learn things, which will be defined by Chuck. But the same can be said for us - we can't learn to fly by flapping our arms because we are not equipped to do it.

Chuck is the (thinking of) writing an Engine which will act as the universe for AIPs (essentially defining the 'physics' of their world, defining their abilities), just as our universe defines our abilities.

I think what Kedaman is pointing out is that, for example, Chuck will have to 'tell' the AIPs under what situations they will make a random 'unpredictable' move. Chuck isn't going to be able to develop a machine that thinks for itself if he defines its abilities. But I can't see how to write a computer program without telling the computer what to do ;)

Chuck - you were right earlier in the thread about history of games. It's not important if you're seeking to emulate human behaviour. If you considered how you play chess for instance, you are not analysing all moves up to this point, you're generally thinking forward from the current point. (i.e. what am I/is he going to do next, given the current position).

Judd you have understood me correct and made my point a lot clearer i think, thanks :)

For instance, a program that would develope strategies for a tic tac toe game, would be equipped with the statespace of all possible moves (reactions to all possible situations in the game) and to enforce good moves, you define static rules that gives value to each possible move. Now the simplest algoritm would be to iterate trough the best moves while playing, and start valuing moves that defeats the computer in game.

Chuck wants to go further and make the program define its own strategies conceptually, this is not at all impossible, as before you just give it the statespace to define all possible concepts - but this would be rather done with logical languages, there's no better tool for a declarative approach. The problem is though how to set the rules for good strategies, empirically testing could take ages - like evolution.

Which is why I think Chuck seems to have cottoned on to the method of getting two AIPs to play together (takes the tedium out of training) (Chuck, I see no reason why a given EXE shouldn't have more than one AIP personality - that would ease the comms problems!)

I think it would be interesting to teach one AIP checkers (for instance), then have it teach another AIP and see what strategies develop - and see if both improve as players. Perhaps the 'player' with the better teacher will always win??

The hard part is programming the 'impetus' - or the 'instinct' (desire?). To a human, the desire to win a game is sufficient to 'cause' us to develop strategies - I don't think that would be sufficient for a computer.

Even with Chuck's current pattern matching AIPs, which seem to learn your strategies, it comes down to simple rules:

1) Can I win on the next move? Yes, then win.
2) No, can my opponent win on the next move? Yes, then block.
3) If I haven't moved already, make the first 'best' move according to my 'win' matrix.
4) If I can't decide, make a random move.

This does however, work brilliantly at simulating intelligent play (probably because that is more or less the way a human would behave).

Once you are out of the pattern matching arena though, it starts to get much more difficult to simulate human behaviour.

Chuck - when you get your checkers engine running, an interesting test would be to teach an AIP, then have it teach another AIP BUT have one or both randomly make unpredictable moves (i.e. randomly decide if a move is going to be random or 'thought out'). I'm not sure if this will lead to stategies developing, but it could have a noticeable effect on learning times...

Misantrop, I'm not exactly sure what you are asking for, but i'll try to answer anyway with what i know.
There's several interpretations of Artificial Intelligence, the branch in computer science that is exploring how computers can act with intelligence is the broadest, but also a bit confusing. Many thinks its about emulation of human intelligence, which might be just a goal in itself, but not nessesarily what makes a machine artificially intelligent. The confusion is the more philosophical issue what to consider intelligent. I have decided to skip philosophical involvement by assuming that intelligence is the vital information processor for finding a solution to problems, thus making it subjectively a tool for the situation, which is of course most practical - Something is intelligent if it can solve my problem. A turing machine can solve all computable problems, in practice all possible solutions to all possible problems, as long as information is what we seek, and once again to avoid philosophy, there isn't anything but information that could make any difference. Whether, you equip the computer with legs, arms and eyes, or integrate your neural network with its circuits isn't changing the information flow between you/your computer.

Some may thus say its intelligent in a context, to me all software is artificially intelligent, I woudln't call anything software in the first place otherways. They fill a function and thus by processing information they solve a particular problem/subproblem

Chuck, Illusion is a tricky word, if there was something that you couldn't reveal later to be something else, it wouldn't be an illusion either, was a mistake of me to use it. Self learning is a word assuming that self is both an information container and processor, in computer science we see this as Object Orienter Programming, a paradigm which puts information in only partly transculent boxes. I'm one of those who think this is a very faulty and dangerous way of programming, the big unknown causing bugs in all programs designed using OOP is the private state that is contained within applications making them act mysterious and spontaneous. Thats an illusion for sure because they do act according to their program, but partly out of control for users as they are granted ownage of their private state.

In declarative languages, the application has a given answer for every question, for a single input you have a single output. The program does not contain any state at all, so the user owns all the information including what requires the program to act as a statemachine. This is how intelligence should be structured, as it can never be unpredictably hostile as in OOP and casually hazardous due to bugs hidden from the programmer.

Self learning to the preserving external state is like centrifugal force to centripetal (in physics we say that centrifugal is an illusionary force) if you compare to human beings, you could say that your memory is part of your senses.

The other thing, although I would prefer beating up other players in UT or even bots (they do act intelligently) to release emotional preassure, well depends of course on the situation, If I talked to my girlfriend instead I would mostly get a lot more satisfaction. That kind of purposeful illusion makes sense, you wouldn't want to play solitaire on your comp if it showed you the cards. In the end we want humans to be happy, not provide them with eternal truths that would probably make them very sad.

Having the "learning" bots playing against each other sounds good, in fact if you experimentally had two human players play against their own bots to train them, and then have them try to beat each other, for a good while, I'm sure the humans would find themselves more oftenly beaten if not even inferior to their bots when they would try to continue their training.

You mentioned desperation, which made me think of something funny, if you had a program that would continously fail, it would gradually loose its resistance to randomly change state in order to evolve, and as a contrast if the desperate bot actually succeeded as a result, it would "feel very good" and add extra bonus points to that strategy. Whats wrong with having egoistic bots, if they're working for you? :)

Chuck: I think we could get a machine to learn to multiply. There are really only two problems. The first is creating a scripting language that is expressive enough to allow the engine to acheive a goal. The second, and more pressing is actually getting the engine to understand the scripting. Essentially, we need a way to allow the engine to store concepts. Even without that, I could probably write program that, given a certain number of operations, could generate a macro to do multiplication, using a search tree method. The problem there is that as the engine is given more operations, the search space becomes immense, and thus, unsearchable, except for the simplest of problems. This leads to a third problem, that of finding a method of solving a problem, given a knowledge base, and a goal state. Not simple problems, but they can be overcome =).

Z.

Z,
I have given thought to the problems you have identified. Absolutely some problems that seem workable to me.

To gain some insight into the matter I conducted an experiment with my wife as the guinea pig. We used some math manipulatives that my wife uses to teach children to MPY, DIV, SQR, etc. I took 8 blocks and put them on a 10x10 grid.

The rules of the experiment were expressed to her as follows:
1. You can count 1 to 100.
2. You can add to produce sums.
3. You can determine row/column position of all blocks.
4. You can take x number of blocks and move them to fill any pattern....any arranging.
5. You can express symetry (i.e. 2 columns with 3 blocks in each column is symetrical).
6. You can express equality (i.e. 1 + 3 = 2 + 2)
You get the idea...

She placed 8 blocks on the grid. I asked her to move them around into patterns using above general rules. She came up with quite a few patterns. Here is a sample:

4 rows with 2 blocks each. Row=4:Col=2. Defined in a AI generated language(script) I wrote it down on paper as:

1+7 = 2 + 6 = 3 + 5 = ... = 8 = Row(4) OP1 Col(2)

AI can develop the last expression above which we would translate as 8 = 4 x 2. Now AI wouldn't know of the label that we associate with it so it uses OP1 as an operation.

Now this concept must be scripted into a text file as you indicate so that will be a definite challenge.

More operations may be something like this:

Pattern(12) OP2 = Pattern(38)

Meaning grid pattern representated by bits is equal to 12. When flipped 90 degrees CW (OP2) it produces pattern defined by 38.

Pattern(33) OP2 Col(2) = Pattern(9)

Meaning grid pattern when shift to the right two columns presents bit pattern equal to 9.

Is this useful? Not sure. But it would be derived information by AI and has value in that fact alone.


Proposed Interface
=============
Now imagine this program has a calculator GUI. It has three text boxes and two buttons (part of button control array).
The calculator is fully functional for three operations: +, - and =. Now, as AI defines the operator above (x), it adds another button and places the caption "OP1" on the button. As soon as this happens, the user can use that function on the button. Now the new knowledge is saved into a file and retrieved each time
the AI calculator problem starts. As teachers, we have the ability to assign new labels to any new math concept created by program. So, the program can now display X instead of OP1 for our benefit. Inside the file, it maintains OP1.
Two grids could be added to show the patterns being manipulated and their outcome.

The brain sees lots of patterns with 8 blocks. However, only a few actually have useable mathematical applications. Others are just interesting patterns. How would AI discrimate between any useful and non-useful stuff? Don't know. Haven't thought that through.

AI Engine must possess sufficent hardcoded functions to define pre-programmed rules. The macro language must be able to define new operations in terms of this pre-programmed language set plus any 'externally' stored keywords or macros.

Now, multiplication will be just one of potentially hundreds of interesting discoveries made by the program. It may not be the first. However, AI programs normally run out of new rules or operations to create after a short while.

To extend its life and usefulness...it could allow for teacher input to teach new concepts based upon what it has learned...allowing it to go looping around and making perhaps more discoveries.

Since I have TTT on the brain, I see this problem as a problem involved with working 2D grid systems. I think AI must be armed to make and record observations about the grid that is storing this bits representing blocks.

Try this. Grab a checkerboard and place a black and red piece somewhere on the board on different cells. Write a list of observations. Start with general observations that a child would make. Then work towards more specific details. For example:
Progression of detail
1: There is a red piece and a black piece on different cells
2: The red piece is above the black piece.
3: The red piece is 3 rows above black piece.
4: The red piece is diagonal to the black piece.
5: Etc.

I think AI must possess basic ability to denote and record these simplistic observations if it going to eventually MPY.

Regarding the search tree method, you are far more familar then I with that method. You know I use bit patterns and comparisons with AIP simply because I was comfortable with that and because I think that method closely approximates human brain at work.


Regards,
ChuckB

Hi Everyone,

Here is a "bit pattern" question.

With grids up to 5x5 I used a LONG integer to store bits using the lower 25 bits out of the available 31 bits (excluding the nasty sign bit) to represent each cell.

Now, to express grids of 15x15, I do not have a SUPER LONG integer. Three ways come to mind however. Please suggest the best and most practical. Are there any other schemes to consider?

1. Grid (15,15) Two indices (row and col) define location.
2. Grid (1 to 225) One index defines cell...using position 1 as the top-left cell.
3. Pseudo SUPER LONG integer using a string to hold at least 225 (15x15) characters.

I have used method 1 above in other game like programs. I must admit, defining patterns meant a whole lot of IF this and this and this and this and this...THEN something. Hardcoding was really tedious. That is why using LONG integers was so nice and easy.

Method 2 more closely matches what I did with LONG integers. I can cloak the arrays into functions so they seem to operate like very long integers. I would have to reduce logic operations such as XOR, AND for example into individual bits...one at a time. Better though then method 1.

Method 3 is where I use strings. An empty grid would have a string gsFree = "1111....1111" (225) of these. Red checker pieces would be something like gsRed=" 0101010101010...00000" (225).

Functions and subs would pass these strings around, extract specific bits using MID( ) and CINT( ) to perform bit logic. Multiplying a string gsRed by 2 would be done by truncating MSB of string and adding a "0" for LSB.

Now I am leading towards Method 3 because it seems to make sense in my head. I am not worried about processor speed.

Regards,
ChuckB

Chuck
You are very eager to accomplish something, I can sense that now, and that is just great, but before you start to rush into any direction you have to ask yourself some questions, I'm not going to answer them, as I don't know what exactly you have in mind, and I don't want to ruin your enthusiasm either.

You are targetting to teach your bot mathematical concepts, there is already mathematical models for all our needs
1. Why would your bot need to learn them?
2. What would it be able to accomplish in your favour?
3. Why are there mathematical concepts?

I could answer on the third one of course, but I want to hear your answer first.

Chuck,

Love the idea of assigning 'boredom' and 'desperation' variables. Could also be neat if the AIP would accuse you of cheating (if it thought you claimed a win invalidly, for instance....)

All adds to the 'illusion'.

I don't think what most people consider to be 'true AI' will ever emerge from programs that seek to emulate human intelligence. We just don't understand our intelligence well enough to replicate it. I think we are far more likely to achieve MI (machine intelligence) through some (as yet) unknown process of allowing machines to self modify their behaviour - effectively reproduce and evolve.

well my simplistic view on AI:
I think humans may program AIs that will act intelligent (the same way we cosider humans to act intelligent), but only within their little system. Now take that to humans: Don't we just act intelligent in our 'little' system? Of course our system (the universe I guess) seems extremely complex to us. Don't you think there are 'things' (very vaguely I know) that might be way out of our intelilgence, maybe so impossible for us to understand that we don't even realize them.
So why shouldn't we archieve AI that is intelligent enough for what we are doing? I doubt there is a need in recreating human intelligence, don't we have enough of those?

I just think that as soon as you mention 'real AI' a lot of people immediately think Terminator , Lt. Cmdr Data or I, Robot :D

I just think that as soon as you mention 'real AI' a lot of people immediately think Terminator , Lt. Cmdr Data or I, Robot :D

kedaman I think Chuck just wants to do this more or less to see if he can - isn't that reason enough?

Quote:

---

Originally posted by kedaman

You are targetting to teach your bot mathematical concepts, there is already mathematical models for all our needs
1. Why would your bot need to learn them?
2. What would it be able to accomplish in your favour?
3. Why are there mathematical concepts?

---

1. Easy. Proof Of Concept. Simple mathematics (such as addition and multiplication) are fairly easy to understand, and, since they are a logical system, should be fairly easy to implement as a test. Once that is acheived, the method could be expanded to just about anything else.

2: Same as above. For the test case, there would be no "practical" value.

3: Eh?

Z.

Judd, sure he can, I am just very uncertain what exactly he wants to accomplish.
Misantrop, the universe you live in is full of tasks that you would consider boring, tedious or dangerous, AI is meant to perform these tasks for you, and some of them are very complicated and require sophisticated software.

Hi Everyone,

K, my personal objectives for my AIP gaming program is to design a program that can learn to play most games that a child of 7 to 10 can create. This will include games like TTT and chess.

Z speaks correctly about proof of concept. I am particularly interested in the time it will take for the program to go brain dead...5 mS, 2Sec, 14Min. I expect a flash of brillance and then a rapid darkhole...measured in a few seconds at most (and that's only because we use DoEvents) ;-)

J is absolutely right...I just want to do it to see if I can...and then if it yields surprisingly useful results I see potential applications for AIP game software.

M refers to our system the universe. My initial plan was to develop a natural language program (NLP) that could chat with my children. Sort of a Turing test for kids. However, I had to define a system or universe that both program and kids could relate to.

This led to gaming. Spend a day with an active 7 year-old and you will know what I mean. There world is wrapped around play.

Now it is conceivable to me that gaming actually introduces people to complex concepts in a natural way without all of the mathematics and lengthy explanations. I see that our model of the world around us can be expressed in terms of gaming. Therefore, AIP that chats and plays games with kids actually possesses the foundation in which we can build a more advanced NLP capability.

J likes the idea of emotion type variables. So do I. They lend to producing random acts of behavior, sudden changes in behavior and sometimes results in lucky decisions.

K, regarding rushing into this...its been five years on paper and in my head...its taken only 6 weeks on this forum for me to actually write what I am thinking (stage 1) in functional code. Without everyones comments and encouragement I may have become discouraged the 3rd time I wrote the AI engine for AIP. Thanks guys!

I am still looking forward to feedback on use of a super long integer using a string to simulate it for the purpose of using bit manipulations to simplify my process. Any experiences are also welcome.

Z, have you had a chance to consider what I said about the experiment above using my wife and also the possibility of a Calculator like panel in which buttons seemingly appear magically as the program discovers new concepts? I am curious to learn more about what you are thinking in this matter.

FINAL NOTE

AI has been a hobby for me...mostly reading lots of books. Generally the persons interested in AI are mathematicians and computer scientists. AI doesn't seem to be a good hobby like fishing or golf for a dumb guy like me. But how do I love it...

Regards,
ChuckB

Chuck this might be 'ahead of the game' (pun intended), but:

My fiancee was doing word searches in bed last night (hmmm...that sounds like I'm denigrating myself ;) ;) ) and I got to thinking abouut other types of pattern matching games that might work with AIPs. Word searches are one - but they don't really have a winner - just a winning condition.

But what about Solitaire (not the card game, the game with marbles)? Again, it's a 'winning condition' game, but I think an AIP could play itself and quickly develop a winning combination of moves (something I never managed with Solitarie!).

I also thought of a couple of other games I used to play as a kid, but I don't know if they have official names.

One was 'Squares' - where you start with a grid of dots and take turns to draw lines. If you complete a square, you claim it and get another go. The person with the most squares when the grid is full is the winner.

Another game was played on a symmetrical board (any shape, but must have an axis of symmetry). Players pieces (I don't remember how many, but the number isn't important) start in identical formations at either side of the board. They take turns to move, one piece at a time, the objective being to be the first to swap your formation to the opposite side of the board. As in checkers, you can only move forward. The game can be modified by allowing/disallowing 'jumps' over one of your opponents pieces(as in checkers).

Then I got to Nine-Men's Morris, Othello etc. etc.

I have a 'medieval' chess game at home too, that is simpler than traditional chess, but still a great strategy game.

Then there is 'Chinese Chess'.

I guess the list is very long....

Z & C

I took the time and read trough most of the posts around here, very quickly but still enough to grasp whats going on. The part which caught my interest was this idea of creating marcos:

Quote:

---

Maybe we can construct a simple program experiment where we define some AI, a goal, some key functions, program self-macro creation ability and see what happens? An example would be to write a program that can add and subtract. Give it ability to write macros...give it comprehension of summing. See if it can learn on its own to create a multiplication macro function on its own...and then use this to discover division, averages, etc.

---

My first question, why would it need to create macros in the first place? The answer i was expecting was to reduce complexity (the amount of operators in the expression). But to counter this, it would just add an extra cost for the reduction, it would still need to do every single operation including the reduction. In practice these concepts have no meaning to the process, just a matter of design. I'm sure this isn't what you were thinking of, so correct me, anyways, i will come back to this at the answer of my third question.

My second question, what would it benefit you if the program invented these concepts. Naturally if it does perform more efficient (which it doesn't) it would benefit you, so I wanted to know if it was in particular interest that you could have use of these concepts.

Third, why do we have mathematical concepts at all? This is the question to draw parallells between how human thinks and software processes information. As humans we have easier to remember well structured information, especially if we can use a couple of basic rules to derive a huge amount of data from, this way of storing information is called abstraction and is the reason why we are so much more flexible than most software, which are only equipped with minimal abstraction facilities. AI, especially with benefit from functional languages especially designed to deal with abstraction, makes it possible to derive similarly large amount of data from a small set of rules. Mathematical modelling is the art of using concepts to express symbolically any form of information processing in similar fashion, and we invented them to help us predict events and thus also achieving and preventing events. If an AI bot would need these, it would be to preserve memory usage.

I'm sorry if I don't really sound encouraging or enthusiastic, but I would be interested if you were going to have it learning mathematical concepts on its own. I'm not such an AI enthusiast like most others here are, but programming is a tedious task, and my goal is similar to AI but using the information we already have to accomplish software without human interference.

Hi K,

I have not read your postings as discouragement. You do talk over my head so it has taken a few days and several readings of your comments to understand what you are saying. Not your fault...I've taught myself to program without formal programming instruction so I missed out on a lot.. :-)

I see you are clearly focused upon the side of efficiency and the use of AI to reduce the tedium of programming. If AI isn't efficient...or doesn't simplify the processing capability of the application...then you ask the question "What's the point?"

I am NOT interested in efficiency. Maybe that disqualifies me from being an AI purist...not sure. But AI in my opinion must benefit humans directly. If it satisfies this requirement then I consider it legitimate.

Consider this from the "human" side of the problem...which I equate as being far more important in most cases.

Question 1
=======
You said the 'macro adds no meaning' to the process. Now this is not right from my frame of reference. Say you use an AI calculator with a +, - and = key. You are limited by those operations for solving math problems. Suppose your AI program very inefficiently and redundantly derives another operation such as x (multiplication). A button pops up on the AI calculator and Voila!...you have now increased your computational power as a human. From the human's perspective, we have just achieved a significant degree of meaning with respect to our ability. Nevermind the wasted CPU computational cycles (technology will soon correct that problem).

Question 2
========
Benefit to the above scenario is straightforward. If you have taken an advanced math exam in college then you will understand that a scientific graphing calculator is far superior to a calculator that only adds and subtracts (although grandfather tells stories of how he used to use an abacus to solve complex physics problems. :-)

Question 3
========
Abstraction? I consider AIP v0.2a to be an excellent experiment in abstraction. My 7 year-old wrote a computer program to play tic-tac-toe with AIP just by using what humans do best...playing. How abstract can I get K?

You say "...my(your) goal is similar to AI but using the information we already have to accomplish software without human interference."

I agree. In the same way that a 'human' must program a computer, humans can 'teach' the computer. Both methods then allow the computer to operate on its own with existing information that does not require human intervention. Macro development as Z and I have discussed definitely satisfies that requirement.

Isn't is cool that we are so much alike? ;-) Keep writing...don't be discouraged if I don't accept traditional AI thinking.

The more and more I study apparently complex things such as colonies of bugs, human DNA decoding, creation of life...I realize that it really isn't so complex as we make it to be. It is all actually much simpler...the problem is we just like complex solutions and algoritms. ;-)

Regards,
ChuckB

Hello C, I'm definitely not trying to discourage you, but I'm rather trying to figure out if it would interest me and also help you if i can.

I have to try and explain more i know, I always want things concise but whats the use if I'm not understood, so if I'm not making any sense let me know :) Let us start from the beginning again and make sure what we don't go to fast.

The vital step you are making is to introduce macros, in order to present new operations to the user, for instance multication, based on addition. Your software can't do it without two things, the need to invent it, as well as inductive reasoning.

A very primitive human, who doesn't know much math at all is introduced to a problem, this person only knows what weight and length is and how to measure length. He can carry certain weight. Now until now he has been carrying blocks of various length, but with fixed height and thickness. By measuing length he can decide if he can carry the piece or not.
The problem is that some pieces are too heavy for him, even though they are shorter than the limit. He figures out that the block height is varying and that this block has more height than most of the blocks. After some inductive reasoning he decides that the weight is calculated as follows:

weight = length + height

well after a while he discovers that this doesn't work either and he has to do more thinking. He finally decides to cut up the blocks into smaller cube blocks all of the same size. and the blocks are arranged 3x4. He understands why the formula doesn't work, and decides he arranges the block into 4 groups of 3, height+height+height+height, and as he can see that there are 4 groups and the length is 4 he decides that there must be a connection. He now knows that he has to count height, length times to calculate the weight, and he decides to call it length times height.

All these decisions are derived from various experiences with all kinds of situations, that doesn't ever occurr to computer program. Even trough testing empirically with incredible processing power, there's no ground to give hints to make these decisions, it took the evolution billions of years to evolve our brains and accumulate the empirical test results in our genes.

What if we just told the AI what to do, F=w*l*h*rho*g (the weight is width times length times height times density times gravity) and exactly how you would calculate with floating point precision, and it could solve all problems of this type. If we transfered all human knowledge over to AI, it could at some point also be able to do empirical guesses as we do.

I can link directly to this thread, but it doesn't appear in the 'Games and Graphics Programming' section.

Tum te tum.

Chuck, I've been trying to figure out if there is a 'perfect' knowledge array for TTT wrt the AIP. Is there one?

I wanted to start with a 'perfect' AIP and have it teach another until they lock onto the tied game, then take the 2nd generation AIP and teach the 3rd generation until tie occurs etc.

Will they all get to the smae tied game?

Hi Judd,
Perfect knowledge array for TTT. The game is pretty limited. There are 8 winning patterns. The center cell is the best because it is related to 4 patterns, corners are next with 3 patterns and the remaining cells intersect only 2 patterns each.

All it takes is for the teacher to play 4 winning patterns before AIP is fully educated. (2 diagonal wins and 1 vertical and 1 horizontal win). It derives the remaining 4 patterns due to its hardcoded ability to recognize patterns (like humans).

AIP stores winning patterns in the file as follows:

ABS(1,1);(2,1);(3,1)=3 'left vertical pattern
ABS(1,2);(2,2);(3,2)=4 'center vertical pattern
ABS(1,3);(2,3);(3,3)=5 'right vertical pattern

As the game progresses, AIP compares the current state of the game with winning patterns and free cells to produce something that looks a bit like this:

100 000 100 = 2
000 010 000 = 1
001 001 001 = 3
=========
101 011 101

The HSum of 2,1 and 3 tells AIP how many moves are required to produce this win. '1' is the answer which corresponds to center vertical column. If the HSums are equal, then AIP examines the VSum. Anything with a '0' is not considered. Usually the highest VSum would be selected.

AIP v0.2 does not use the history data at the top of 3,4 or 5. This means that in AIP's experience, the right vertical column had the better chance of winning. This would be valuable against a human because as humans we have our predicatable patterns and ways of doing things. A computer program would not have that bias and therefore historical data may not be so important.

Now, v0.3 will have these two improvements: 1) use historical data to force AIP to decide in the event that all VSums are the same value or all HSums are the same value or 2) after playing the same moves for 2 consecutive games, it will randomly pick a different move in order to break out of the mold.

Therefore, experience (playing lots of games) will lead AIP to learn more winning patterns and to collect statistical data on what patterns seem to win the most.

With these improvements we will see different strategies emerge but eventually I believe the AIP teacher and AIP student will continue to tie.

Judd, here is the problem that need figuring out. I am looking ahead at v0.4 that will hopefully play checkers/chess. Teaching a program to learn moves will be relatively easy if I model it after a human being. The difficult part, which I have not figured out, is how can experience (playing lots of games) make AIP smarter and smarter...eventually playing at a level as a grandmaster (...now I am in fantasy land...just humor me)? You see, this generic algorithm must be hardcoded in advance. TTT was easy...this whoops up on me.

Now I am thinking this...

perhaps AIP will begin stringing moves together to complete a goal. For example, it takes two moves of a knight to capture a piece that is normally out of range...or a piece can be made to block, capture, sacrifice or trap.

Kedaman, I haven't forgotten your last post. I'll respond shortly.

Regards,
ChuckB