Recipe for Thesis

On the other day I visited one Restaurant in Gwalior. It is famous for its vegetarian food. Me and my friend were having a discussion on thesis presentation and its after effects. Then one idea clicked in my mind that completing thesis is similar to making a dish. In last post I told you what human mind is capable of, when it comes to thinking process. Don’t worry I won't baffle you by starting again. So coming back to the topic.

My dear friends completing your thesis work is sort of cooking delicious food. Add the required ingredient in proper quantities and proportion it becomes more delicious. Here ingredient refers to publishing the paper in journal, international or national conference

One of my friends, in last post suggested me that i should not divert from the central idea. So my dear friend this time I am not going to do tat .. so keep reading

Similarity between Culinary recipes and Thesis completion::

1)The name of the dish, similar to that Deciding Topic, is the first important thing. It is said in a research work if you have decided your topic, then half your work is already done.
2)Second step is to write down how much time it will take to prepare the dish. This is variable in case of dishes. On the other hand thesis work is generally given 1 year as per Indian Education System.
3)Third step is finding the required ingredients for the dish, along with their quantities and proportion. Here old research paper and previous thesis work play the role of ingredients. You have to select the best ingredients for your thesis.
4)Equipment and proper environment is needed for preparing the dish. Similarly you have to decide what tools and language you are going to use. For research you can use already available tools such as Matlab, NS Tool, minitab etc.. , or you can write your own code in any of your favorite languages.
5)Recipe includes an ordered list of preparation step. The ordered list is our Algorithm.
6)Texture and flavour : Again different people have different tastes, so is the case with reviewing panel. One of the great teachers told us that giving final Thesis presentation is similar to making juice. Simple juice (without publication) is just ok , but if you add some flavor (publish somewhere in conference) it tastes good. Adding Cherry (publishing in some international conference) makes it more delicious and tasty. But if you make Shake instead of juice (by publishing it in some Good journal ) then of-course your shake is best in the market. What basically he was trying to say is that until it has been approved by a third party, it is not upto the standard.

PS: Above mentioned recipe is subjected to take a long time, so do what we are good in doing.
“To steal ideas from one person is plagiarism, to steal ideas from many is research.”

I can only say that an intelligent person just needs a sign.

STATUARY WARNING from one of my friends ::
this blog post does not tell you the recipe, methodology, styles, etc. for writing of a research paper. scholars, academicians, students, and all other people who are trying to search for articles/posts related to the said areas may kindly keep away. others are free to read and comment.

Good Quotes / An Apple

Gandhiji's 3 monkeys are famous for three main message for live - See no Evil, Hear No Evil, Speak No Evil. These are 2,500 year old Chinese code of conduct. The three monkeys are Mizaru, covering his eyes, who sees no evil; Kikazaru, covering his ears, who hears no evil; and Iwazaru, covering his mouth, who speaks no evil. I don’t know how Gandhi ji and these 3 monkey get associated together. Finding asking for this question, I come to know that Mahatma Gandhi had a famous 3 monkey’s porcelain paperweight, which he kept by his bedside. This might help him to remember how man should conduct himself. Thinking of these three monkey, my head echoes my three school friends, when-ever and where-ever they got any chance to click, they pose themselves as Gandhi ji's three monkey.

Now you are definitely thinking that why I am boring you by narrating the story of three monkey. Actually I was thinking to write something and you all know what human mind is capable of when it come to thinking process. You just have a thought and in a flash your mind can take you to the acem of the Everest, in another flash u find yourself in the abysmal of Pacific ocean; for one second you are on earth and another you r floating in universe (Now you can see yourself .. once you let your mind free it will take you anywhere) I seem to be getting distracted from the topic, so stopping that now. Returning back, I was telling you why i am baffling you with this post. I was going through my friend's blog that kinda remind me that i didn't post my thoughts since long back. In mean time I got job,my bro got selected in IES etc... many things happen So the world seem more fun now. Again i am diverting from topic. But mind is not under my control .. you can see that .. Only saint can control it. and i am not among them ..

So I was writing about Role of Quotations in our life. To support this I have to add that Good Quotes is similar to consuming an apple daily as precispiced by doctors. The only difference is that the first one is necessary for internal body and soul; latter one is good for health. I have three Poster with following quotations

“THE BUSINESS OF LIFE IS TO GO FORWARD…”

“BE A GOOD e a Good Finder, look for the good in others.”

“..माँ का वात्सल्य , अटूट विस्वास”

These quotation really help in my up and downs, because when you are in down- state there Quotations help you think in +ve manner. Show ray of hope. Now I must admit that Putting a poster in a room surely influence behavior of people around it in some way as you come around it 100 times a day. I assume that the concept of marketing or Advertisements “If you keep on hammering people with your whatever product continuously, at least they know your product” has been taken from here only.

Coming out of this HALWA’s-concept. Here Halwa’s refer to MBA. There a different story why MBA is Halwa (Many of you know the reason, for rest I will tell you some other time.) So summing up this discussion, I am sure that by now you somewhat realize the importance of good thoughts in life. And of course I am not stopping you to eat an apple. It would be better if you can consume both. I will be Good for healthy mind and body.

Enjoy some

”Dream is not what you see when you sleep…It’s the thing which does not let you sleep” Dr. A.P.J Abdul Kalam – 11th President of India

"Innovation distinguishes between a leader and a follower."

I AM SATISFIED BY THIS LIFE .........I NEVER COMPARE MY LIFE WITH OTHERS COZ I REALLY DON'T HAVE ANY IDEA OF WHAT THEIR JOURNEY IS ALL ABOUT!!!

असफलता एक चुनौती है, इसे स्वीकार करो,
क्या कमी रह गई, देखो और सुधार करो.
जब तक न सफल हो, नींद चैन को त्यागो तुम,
संघर्श का मैदान छोड़ कर मत भागो तुम.
कुछ किये बिना ही जय जय कार नहीं होती,
कोशिश करने वालों की कभी हार नहीं होती |

हर गम को पला नहीं जाता,कांच की चीजों को उछाला नहीं जाता ,

कुछ करना है तो म्हणत करो, हर बात को "AL IZ WELL" बोल के ताला नहीं जाता |

Reinforcement Learning ( Part 2..)

Element of reinforcement learning

Agent:

• the general aim of Machine Learning is to produce intelligent programs, often called agents, through a process of learning and evolving.

Environment:

• All external condition that effects an agent is included in environment.

Policy:

• It is the set of rules which defines the agent’s behavior at a given time in a particular environment condition.

• It direct the help in mapping from states to actions.

• In some case the policy may be a simple function or lookup tables.

• It is responsible to determine behavior

Reward function:

• It basically defines the goal in a reinforcement learning problem

• Maps from states, state-action pairs, or state-action- successor state

• The policy is altered to achieve this goal

The sole objective of a reinforcement learning agent's is to maximize the total reward it receivesin the long run (returns).

Value function:

• Reward function indicates what is good in an immediate sense while a value function specifies what is good in the long run.

• Value of a state is the total amount of reward an agent can expect top accumulate over the future, starting form that state.

Model of the environment :

• predicts the mimics behavior of the environment

• used for planning

• if we know the the current state and action then model predict the resultant next state and next reward.

For example given a state and action, the model predict the resultant next state and next reward. Model are used for planning . By which we mean any way of deciding the set of action by considering possible future situation before they actually experience.

Agent-Environment Interface

The "cause and effect" idea can be translated into the following steps for an RL agent:

1. The agent observes an input state
2. An action is determined by a decision making function (policy)
3. The action is performed
4. The agent receives a scalar reward or reinforcement from the environment
5. Information about the reward given for that state / action pair is recorded

Reinforcement Learning is learning how to act in order to maximize a numerical reward signal.

RL is learning from trial and error interaction with the world.

Eg : Cycle Learning is a good example of the reinforcement learning . The goal given to the Reinforcement Learning system is simply to ride the bicycle without falling over. Its only the experience which teaches a person how to ride a cycle. Initially the person performs a series of actions such as tilting their handle at 45 degree to right than if they fall down it give a negative feed-back that tilting this side is wrong. Similarly they try for left side and again get a negative feedback. By performing enough of these trial-and-error interactions with the environment, the RL system will ultimately learn how to prevent the bicycle from ever falling over.

Reinforcement learning is not a type of neural network, nor is it an alternative to neural networks. Rather, it is an orthogonal approach that addresses a different, more difficult question .i.e learning through experiences similar to human being.

Following are the some silent Features of Reinforcement Learning :

• It is a set of problems rather than a set of techniques
• RL brings a way of programming agents by reward and punishment(negative reward) without specifying how the task is to be achieved.Based on trial-error interactions

“RL as a tool” point of view:

• RL is training by rewards and punishments.

• Train the computer as we might train a dog.

The learning agent’s point of view:

• RL is learning from trial and error with the world.

• Eg. how much reward I much get if I get this .

Evaluative Feedback

The most important feature distinguishing between Reinforcement Learning and other type of learning is that RL uses evaluative training action , in-spite of instructive.

Purely evaluative feedback indicates how good the action taken is, but not whether it is the best or the worst action possible. Evaluative feedback is the basis of methods for function optimization.

Purely instructive feedback, on the other hand, indicates the correct action to take, independently of the action actually taken.

Eg: supervised learning is instructive

Associative and Non Associative Tasks:

Associative: Associative tasks are situation dependent. Input mapped to output. It involves both trial-and-error learning in the form of search for the best actions and association of these action with the situations in which they are best.

Non Associative: situation independence. there is no need for associating different action with different situation. Learn one best input. The learner tries to find a single best action when the task is stationary or tries to track the best action as it changes over time when the task is non stationary.

Reinforcement Learning (Part 1. )

"What reinforcement we may gain from hope; if not, what resolution from despair. "

Reinforcement learning is kind of machine learning. So before going into the depth of Reinforcement learning , first see what is machine learning .

Machine learning: Definition

Machine learning is a scientific discipline that is concerned with the design and development of algorithms that allow computers to learn based on data, such as from sensor data or databases. A major focus of machine learning research is to automatically learn to recognize complex patterns and make intelligent decisions based on data .

Machine Learning Algorithms :

With respect to the feedback type to learner, the machine learning can be divided into three groups :

• Supervised learning — In which the algorithm generates a function that maps inputs to desired outputs. We have both input and output. We can say that Supervised learning is task driven . It basically deals with classification.
• Unsupervised learning — An agent which models a set of inputs: labeled examples are not available. Here we try to make cluster of similar type of data and then fed them to the Neural Network. The neural network proceed until it reaches to a certain minim error or a predefined epochs. Model is prepared once in the starting of learning. It is data driven . It basically deals with clustering.
• Reinforcement learning — This approach is very close to human learning. In Reinforcement learning the algorithm learns a policy of how to act in a given environment. Every action has some impact in the environment, and the environment provides feedback in the form of rewards that guides the learning algorithm.

Difference in Supervised , unsupervised and Reinforcement learning???

Supervised learning is task driven, that in advance we know that for a particular input what is the output, It basically deals with classification.

On the other hand in unsupervised learning is data driven i.e input is not mapped to the output . It basically deals with clustering.

While Reinforcement learning emphasizes learning feedback that evaluates the learner's performance without providing standards of correctness in the form of behavioral targets.

The following example will explain u more :

Supervised Learning

Step: 1
Teacher: Does picture 1 show a tree or a bird ?
Learner: A flower.
Teacher: No, it’s a tree .

Step: 2
Teacher: Does picture 2 show a car or a bike?
Learner: A car.
Teacher: Yes, it’s a car.

Step: 3 ....

Reinforcement Learning

Step: 1
World: You are in state 4. Choose action A or C.
Learner: Action A.
World: Your reward is 100.

Step: 2

World: You are in state 27. Choose action B or E.
Learner: Action B.
World: Your reward is 50.

Step: 3 ....

so we can say that reinforcement learning doesn’t tell that the action is best of not. It only tell if it is good or bad by assigning scalar rewards .

Meaning of Reinforcement:

The occurrence of an event, in the proper relation to a response, that tends to increase the probability that the response will occur again in the same situation.

So we can define Reinforcement learning as a problem faced by an agent that learns behavior through trial-and-error interactions with a dynamic environment. Reinforcement learning emphasizes learning feedback that evaluates the learner's performance without providing standards of correctness in the form of behavioral targets.

The best example of reinforcement learning is Bicycle learning

"GO" :: Google Programming Language

GOOGLE Ready Steady and GO GO ... GO...

So here comes a great news .. Google had launched an entirely new programming language "GO" on November 10, 2009. GO is considered as the new programming language that provide solution to existing language such as C++ and Java. GO is released under an open source licence. At the moment Go is only available for Linux and Mac OS. The company know the power of open source. This new language Go has been in development phase for last two years, releasing Go under open source license, Google hopes that the open source community will develop and build Go into a viable choice for software development. Just last week only this Search giant released its Closure JavaScript tools for building Ajax web apps. And now Google has considerably upped its investment in free software with the release of Go, which is an entirely new programming language.

What is the need of New language

No new language in last decade, but lot has change like the libraries got bigger and bigger so as dependency chains. Network has change a lot but language doesn't reflect that. So the case with system space client server. This also happen in case of CPU. computers are now having Multicore, Multichip while the language we are using doesn't have this concept while development. It take too long to build software. Dependencies are uncontrolled. Yet Machine got more, but stopped getting faster. Machine has more processor, but the clock speed doesn't change as much. So the speed of developing a software is still a slow process.

Mr Pike said "If we stay as we are, before long software construction will be unbearably slow"

Now the question is can't we change the existing language as per our demand. The answer is no. If we made change in current language, we have to rewrite the libraries, it might be take in wrong direction. So its better to develop a new language which is much faster and fun to work with.

Whats new in "GO"

GO is considered as one of the branch of C, the mother language of all language. At first glance, Go looks a bit like C, but borrows some elements, such as garbage collection, from scripting languages like Python and JavaScript. It is bigger then C, but lesser then C++.

In "GO" concept are orthogonal for-example the concept of interface and implementation is completely orthogonal. they doesn't interface each other. Grammar is regular and simple with few keywords and it is parsable without s symbol table. It is more object oriented than C++ and Java.

Dependencies is one of the important feature of the GO.

say A.go depends on B.go and B.go depends on C.go.

Then in usual way the complier will compile in a reverse order C.go, B.go then A.go, while this is not the case with GO complier. To compile A.go compiler reads B.o object file not C.o as B.oas everthing that needs A.go.

Concurrency is the another important feature. Go provide a way to write system and server as concurrent, garbage-collected process(know as go-routines) with support from language and run-time. In lay man language go-routine is some what similar to thread or process.

Following are some the snapshot that describe basic and program structure of GO language





It's the speed that differentiate Go from other programming language. The following video shows a demo that shows the entire language — over 120K lines of code — compiling in under 10 seconds.



Benefit of "GO"

Being a giant in search engine, Google priority is to provide the service in a faster and more reliable way. Go is intended to be used for developer applications like, web servers. In fact, the golang.org website is being hosted by a Go program.

Google believes that the web and computing have changed dramatically in the last ten years, but the languages powering that computing have not. But when you get down to it, Google could benefit a great deal from not only having a more efficient programming language, but having one it designed being used in thousands web and software apps.

If you’d like to learn more, check the above video of Pike’s tech talk or check the Go website(http://golang.org/).