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I understand that an algorithm is a set of instructions. Ai is essentially the same thing, only, more complicated? Let's say I use a minmax algorithm to allow moves to be played on a tic tac toe board, generally people would consider this ai. But if I implement an algorithm to solve a rubiks cube, is that considered ai?
I guess what I'm asking is, is it the complexity of the algorithm, the fact that situations change on the fly in an algorithm, the ignorance of the user/programmer as to how the algorithm works or all/some of the above? Or am I missing something?
I feel like this field is quite arbitrary. I imagine for good reason.I imagine because complexity is complex.
It is indeed quite arbitrary.
If you consult wikipedia you might find following definition which in my personal opinion catches the load quite accurately:
Computer science defines AI research as the study of "intelligent
agents": any device that perceives its environment and takes actions
that maximize its chance of successfully achieving its goals. A more
elaborate definition characterizes AI as "a system's ability to
correctly interpret external data, to learn from such data, and to use
those learnings to achieve specific goals and tasks through flexible
adaptation."
To take your Rubiks Cube as an example, there would be at least 2 ways you could write the algoritm to solve the puzzle. Firstly, any cube can be solved by following a hardcoded path or set of instructions once you have a certain start position. Implementing this would not be considered AI in my opinion as the machine itself is not learning anything. It just follows a well defined path of instructions till the end.
A second way to implement this would be to have the program just start solving it randomly. But the machine remembers it's moves, and learns the most effective path to reach the solution. When solving the next cube, the machine can build upon this newly learned information to solve it faster and again learn from this iteration to improve it's algorithm.
So in short, as far as I'm concerned, it can be considered AI when a machine is capable of optimizing/extending its own algorithms to become more efficient in its tasks.
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Is there a way to estimate the energy consumed by a program on an ARM CPU? In embedded systems, energy consumption is one of the most important parameters and I was wondering whether it is possible for a programmer to know approximately how much energy is needed to run the program?
For example, since on the ARM CPU division executed on multiple cycles I imagine that a code using divisions would consume more energy than a code that doesn't. But this reasing is quite intuitive, is there a better way to qulify the energy consumed by a CPU when executing a code?
I don't think there are any ARM-specific tricks here (and 'ARM' covers umpteen different things anyway). You usually look at the current consumption in the various different power states you use (run, sleep, etc) and then estimate what proportion of time is spent in each state. This lets you calculate average current/power.
It doesn't usually make much sense to say 'this instruction uses a lot of power' - what you might instead care about is 'this sequence of instructions take a lot of time to run, hence I can't get back to sleep quickly'.
Closest you'll get with off the shelf tools is something similar to http://ds.arm.com/ds-5/optimize/arm-energy-probe/
Generally battery run systems have fuel gauges which are exposed through sysfs entries and can provide how much current is passing by. Think it like smart phone battery/charge indicator. Those are generally not that reliable and hard to correlate with exact time of application run, but may give you a rough estimate.
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I have been given a task to write a C language analyser using an AFD. I can choose whichever language I want so I think I will go for Ruby. However this task is a little overwhelming to grasp at the beginning.
The problem I stumble across is : How do I even represent the AFD of the entire C language?.
I have been doing a little bit of digging and I ended up reading this on lexical analysis. In this paper the author defines every token of the language as a transition between 2 states (which is very logical). I find it almost impossible for me not to miss a few or build such a big AFD by hand without many mistakes. Any tips ?
The task you have is a similar one posed to many undergraduate students in compiler courses every year in thousands of universities, and the notes you cite are good sample of the many sets of course notes available on the topic.
The solution is the same as any software engineering problem: testing against the specification.
Although the intellectual problem of the analysis and creation of AFDs for a whole language by hand might seem overwhelming error prone, don't forget you are tasked with also implementing this (in your chosen language of Ruby).
This implementation can be tested by feeding it carefully graded and selected samples of C language input. When it does not deliver the expected result there error will either be in the coding of the AFD or a fault in the AFD you constructed. You make the necessary change and go around the testing loop again.
You will eventually end up with a valid AFD for the entire C language and an analyser for it written in Ruby.
It is often a good idea to start small and implement a subset of the C language and get that working first and then add more to it using stepwise refinement. This is a less risky strategy than attempting to do the whole thing in one go.
You need to apply all those techniques you should have learned about building specifications, designs, programs and testing and apply it to this problem. Just apply good computer science and software engineering to this problem.
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I tried to find a good place to ask my question, which isn't programming, though it implies programming in C.
Our schoolteachers told us that we need to start exercise our programing skills, in C, based on math exersices. Even if I search the web for the best ways to solve such exersices and I came up with the Math library [<math.h>] I couldn't find a good page with many examples of solving exersices. My best course so far is Wikipedia but I can understand the fact that the Wikipedia can't store all the functionalities the library gives. I even looked in some examples want to find a complete coursebook for sovling all good math exersices we can make with a paper and a pen!
Have anyone any good idea?
So, you are trying to learn programming to solve math problems, that's good. But, I think you are getting a wrong idea about programming, Programming does not solve problems for you. To solve a problem, you have to decide on an algorithm to solve a problem and then create programmatic statements, in whichever language you like, then the program that you have created will give you an outcome based on the algorithm. You have to take the outcome and then decide yourself for further study.
for example
finding a factorial of a number
int i = number;
fact = 1;
while(i > 0)
fact * = i;
this way you will get a factorial of the number you specify, It is you who has to decide whether your algorithm is working fine, by comparing it with manual work, or with records. As you can see, the above program is an infinite loop and it is me who has to debug such issues, the program does not do that. Then What does a program do, it just automates what you do manual and help you save time and improve efficiency at work.
So to solve exercises, you have to understand problem statements and then script a program. I see you are talking about math library, we have good resource online to study important math functions which are highly useful, for in depth understand of their working open up the library files and study.
A Program can never solve your problem without you writing it, and deciding on its efficiency
See if this cmath solves you problem.
Header <cmath> declares a set of functions to compute common mathematical operations and transformations
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Merge sort application
Can anyone tell me what does online sorting means?I could not find perfect answer.
Source : http://en.wikipedia.org/wiki/Merge_sort
Thanks in advance!
Quicksort gained widespread adoption, appearing, for example, in Unix as the default library sort function, whence it lent its name to the C standard library function qsort and in the reference implementation of Java.
Merge sort type algorithms allowed large data sets to be sorted on early computers that had small random access memories by modern standards. Records were stored on magnetic tape and processed on banks of magnetic tape drives . merge sort is implemented with disk drives.
For more read : http://en.wikipedia.org/wiki/Merge_sort
http://en.wikipedia.org/wiki/Quicksort#References
Their applications vary; it depends on the size and contents of what you're sorting.
Quicksort is one of the fastest sorting algorithms, so it is commonly used in commercial applications.
Merge sort is used mostly under size constraints because it isn't as hefty an algorithm as Quicksort.
Both algorithms can be used in distributed systems for sorting data.
Merge sort is a typical example used in online sorting.
On the other hand quick sort also has some usage in graphic/game development where u need to sort data points and cluster them out.
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Just out of curiosity, assuming there exists a software life form. How would you detect him/her? What are your criteria of figuring out if something/someone is intelligent or not?
It seems to me that it should be quite simple to create such software once you set the right target (not just following a naive "mimic human->pass Turing Test" way).
When posting an answer try also finding a counter example. I have real difficuly inventing anything consistent which I myself agree with.
Warmup
First we need to understand what a life form is.
Take this explanation, for example:
An entity which exists and tries to continue its existence through nourishment or procreation.
If we accept this explanation then in fact many programs represent a life form.
They exist, that's obvious. They attempt to continue their existence through opening child processes, surviving in persistent data storages and continuing the next day.
So, here we are, among digital life forms around us.
On the other hand, there's the idea of evolving and being sentient.
With evolving, it's easy. Many programs have been written to be able to modify their body to adapt to certain scenarios. Computer viruses are first examples of that.
With sentience, it is a different story. An entity needs to be aware of its existence, understand itself and the environment around it, also take active decisions on its life activities.
A computer program has nothing of that kind. In fact, if it still applies, the scientists haven't figured out the definition of "being aware of itself" and consciousness. So until we know what that means, we can't attribute that quality to an entity or the other way around, to take it away.
The bottom line is, you can argue a computer program to be a life form, but it does not qualify for a sentient being.
Thinks humanly, acts humanly.
OR
Thinks rationally, acts rationally.