Category: miscellaneous

hmmm … who comes here from the NASA?! Do you want to steal me to make intelligent robots for you?! 😀 You may mail me at SoloGen at [domain-name of here]. (;

The Iranian Government has systematically and methodically denied Iranians the ability to speak freely and communicate with each other and with people outside of the country, through suppression of the national press, television, telephone calls and now the Internet. The free expression of ideas and opinions is cherished by Iranians, and we hold this to be a fundamental human right. We condemn all efforts by governments and telecommunication firms both within Iran and outside of the country who implement restrictions to the free exchange of speech and ideas.
You, dear reader, please sign this petition against Internet censoring in Iran.

Happy New Year!

“To the best of the author’s knowledge …” = “WE WERE TOO LAZY TO DO A REAL LITERATURE SEARCH.”
“Results were found through direct experimentation.” = “WE PLAYED AROUND WITH IT UNTIL IT WORKED.”
“The data agreed quite well with the predicted model.” = “IF YOU TURN THE PAGE UPSIDE DOWN AND SQUINT, IT DOESN’T LOOK TOO DIFFERENT.”
“It should be noted that …” = “OK, SO MY EXPERIMENTS WEREN’T PERFECT. ARE YOU HAPPY NOW??”
“There results suggest that …” = “IF WE TAKE A HUGE LEAP IN REASONING, WE CAN GET MORE MILEAGE OUT OF OUR DATA.”
“Future work will focus on … “ = “YES, WE KNOW THERE IS A BIG FLAW, BUT WE PROMISE WE’LL GET TO IT SOMEDAY.”
“…remains an open question.” = “WE HAVE NO CLUE EITHER”.

(copied from a comic from www.phdcomics.com, drawn by Jorge Cham if I read it right!)

I’ve started ranking schools with AI researches. My emphasize is on new-age AI, e.g. situated embodied intelligent robots, neural networks, machine learning (especially reinforcement learning) fuzzy systems, evolutionary computation, pattern recognition, vision, and … . It means that I do not score schools with symbolic AI approach much. In other words, I score universities which is along my preferences. I’ve divided schools into these 6 categories:

5: Everything is pleasant: good projects, good professors, good reputation of school.
4: Very good place; may be not too prestigious.
3: Somehow good, e.g. one or two well-known professors but not a famous school.
2: Hey! There are trying to do something!
1: There is a little AI there, i.e. just having the name.
0: Nothing!

I will report the results after finishing my applying and receiving admissions. Universities can increase their rank by giving me admission with financial aid!

Hey! Is there anybody out there, want a new student, a very good one, a creative one?! Come on!! You earn much!

Ramin replied me back and wrote:

Every program could be considered as an automata which gets a string input and outputs a string output of codes. I think the robustness of algorithms can be interpreted as “redundancy” in this messaging framework. Thus, I recommend this, as an alternative strategy, to bring robustness to computer algorithms from the communications view point.

The idea of translating computer algorithms to dynamical systems is fascinating but first, we should reconsider the “dynamic” properties of our algorithms.

And I wrote him:

You mentioned a very good and interesting point. I wonder if there is a relation between dyamical properties of the system and information content of the message. I guess that the fractal dimension of a trajectory of the system’s output has a relation with output signal’s entropy. Consider this: a stable system converges to a single point in the state space (or output space) (fractal dimension = 0) and the entropy of the output signal converges to the zero as knowing the system is stable is equivalent to knowing what its future would be. A limit cycle leads to a finite fractal dimension (e.g. in 2D state space, it is between 1 and 2), and the entropy of it is finite depending on the length of its descriptor string, and etc.
Properties like robustness may be considered as cross-entropy between source (disturbances) to destination (output signal). hmmm … it is interesting in my mind. Maybe we are reinventing cybernetics!

You are writing a very advanced algorithm and it looks that you have noticed to every aspects of implementations, but your program does not work at all! You may become disappointed of the performance of your advanced algorithm, or you might find a very small bug in a line of your code: you had typed x++ instead of x–. The world would be a better place to live if your programs were not that sensitive to these small typos.
Not very seriously, I have thought about robust algorithm, i.e. an algorithm that is insensitive to its changes. Is it possible?! To answer this question, I must know what is an algorithm and what can be considered as an algorithm. I think (however, I am not sure), an algorithm can be considered as a thing that can be implemented by a Turing machine and vice versa. This remains the big question that is about the limits of a Turing machine. I know that it is a universal computer, but I am not sure what is the exact meaning of it: does it mean that every mathematical calculation (e.g. solving a PDE) is a “computation” task and can be implemented by a Turing machine. In addition, I want to know if there exists a problem that cannot be implemented by an algorithm (you know, I have not had any course on theory of computation or something similar).
Let’s assume that an algorithm is a sufficient framework for almost everything, including solution of a dynamical system. If the converse is true, a dynamical system is capable to present an algorithm and is its equivalent, is it possible to use the same robust analyses of the dynamical system to an algorithmic one? For instance, we may analyze a specific algorithm to see whether it is robust to some small changes or it would become unstable? If x(n) is the state of an algorithm at moment “n” and x(n+1) = F(x(n))+G(x(n),u(n)) is the next state, we may present a perturbed version of it as x(n+1)=F(x(n)) + deltaF((x(n)) + G(x(n),u(n)) + deltaG(x(n),u(n)) + du(n). These deltaF(.) and … can be considered as perturbations and the stability of the new system is dependent on their properties. For instance, for the following algorithm:

Get inputs x(1) … x(k)
Sum = 0;
for(i=1;i

I watched I, Robot a few days ago. It was of the kind of science fiction movies that pleases me much (like AI, Terminator II, and even 2001:A Space Odyssey). I don’t want to describe the movie; however, I want to say that those kinds of problems are inevitable and are side-effects of the singularity which I believe in. It is not because of disobeying those three robotics laws of Asimov, but due the fact that the agent’s designer doesn’t know what kind of intelligent behavior emerges from the interaction of an embodied system equipped with a sufficient processing power and necessary information processing software.

Which OS are You?

Which File Extension are You?

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