Sensor API for Symbian OS

• It appears that in order to access accelerometer data, Sensor API must be used. Sensor API is available in S60 5th Edition SDK (Nokia N97). Nokia N96 has S60 3rd Edition SDK FP2, so the Sensor API plugin must be installed.
• Here is a cool template plugin for sensor specific projects in Carbide.C++
• Here is an excellent explanation of the features in Sensor API

Hello World, Console Application

1. The International Mobile Equipment Identity or IMEI number is needed for using SymbianSigned online service. Type *#06# on the phone and the number will be shown.
2. Check your phone's date and time, adjust it if needed.
3. Append "FR, RI" (File Run, Run on Installation) in the pkg file after exe-file's path

Seed Idea

I believe that one must have some seed idea upon which to build considerable amount of work and produce something concrete at the end. I should stick to my first and only idea, ePet and build upon it whatever is needed in the best possible way to deliver its potentials. For example what can be the mathematical formulation of the idea and what are the practical limitations, can be a line of research. For a start, I should build a working application of ePet in Symbian C++ and test performance based on various criteria.

Confession

During my undergrad, I had been (foolishly) caught up with my adolescent love, the idea of studying Physics. The idea that somehow at the end I will be studying String Theory never left my mind. I started studying things in Computer Science at a very late stage and failed to pull up much by the end. I thought it would be better to work in a software farm to learn something about coding in big projects which I severely lacked by then. I guess that was not a bad idea. I always looked at PhD as a period during which I could be as creative as I wish. Yet thinking about the gaps and delays along my way, I was not at all initiated to pursue a PhD. I was thinking about doing some other kind of creative work, e.g., writing seriously or even working for a theatre. Meanwhile, I registered and appeared for GRE and TOEFL almost out of whim of the vogue. And in between GRE and TOEFL, I approached an offer for PhD, without giving much thoughts to what actually I would be doing. In retrospect, I made many thoughtless decisions. I don't want to get a PhD as a respected degree only, I want to completely lose myself in something great. For now, I don't see much future to that end, so I have decided to stop here.

Something About Logic

1. Invalid solutions to quadratic equations: I remember, we had to solve some maths in Chemistry which usually yielded two solutions, one of them would be absurd. I always wondered why one of the mathematically derived solutions should be absurd in reality. One reasoning could be, the mathematical modeling of the reaction scenario is more general than what was needed; so, not all solutions are applicable for the Chemistry scenario. What about those quadratic equations where if you put one of the solutions in, the mathematical equation is not satisfied! It can be understood through logic. Both of the solutions to the quadratic equation are valid only when every next step in the solution-procedure is an 'if and only if' or bi-directional implication. For example, x + 2 = sqrt(4 -x) has an absurd solution where x = -5. Putting x = -5 in the left hand side of the equation gives -3 whereas in the right hand side gives 3. For when we square the equation on both sides, we have a unidirectional implication or the 'if' part only: x+2 = sqrt(4-x) implies (x+2)^2 = 4-x, but not the other way around.
2. Deductive vs. Inductive Reasoning: Deductive Reasoning is based on premises and logically arrived upon conclusions, whereas Inductive Reasoning is based on examples studied so far: 'I have seen this event in 1000 cases and I say it will also happen in the 1001th case.' Mathematicians do not consider Inductive Reasoning as a form of proof in contrast to experimental scientists who are usually reasonably (due to practical limitations) satisfied with Inductive Reasoning backed up by some number of experiments. Yet we should always keep in mind that there is no categorical reason to expect that the 1001th case will be similar.

Reading List: Game Theory and Bounded Rationality

Game Theory:

1. A Course in Game Theory. Martin J. Osborne and Ariel Rubinstein
2. Game Theory. Drew Fudenberg and Jean Tirole
3. Models in Cooperative Game Theory. Rodica Branzei, Dinko Dimitrov, and Stef Tijs
4. Game Theory Evolving. Herbert Gintis
5. Algorithmic Game Theory. Noam Nisham, et al.
6. Playing for Real: A Text on Game Theory. Ken Binmore
7. Grey Game Theory and Its Applications in Economic Decision-making. Fang et al.
8. Game Theory: Analysis of Conflict. Roger B. Myerson
9. Game Theory: A Multi-level Approach. Hans Peters
10. Essentials of Game Theory. Kevin Leyton-Brown and Yoav Shoham
11. Theory of Games and Economic Behavior. Neumann and Morgenstern
12. Essays on Game Theory. John Nash
13. Multiagent Systems. Yoav Shoham and Kevin Leyton-Brown
14. Thinking Strategically. Avinash K. Dixit and Barry J. Nalebuff
15. Strategies and Games. Prajit K. Dutta
16. Strategy. Joel Watson
17. On Numbers and Games. John Conway
18. Winning Ways for Your Mathematical Plays. Erwin Berlekamp et al.
19. Incomplete Information, Repeated Games, and N-Player Games. Evelyn C. Fink et al.
20. Repeated Games with Incomplete Information. Aumann and Maschler
21. A First Course on Zero-Sum Repeated Games. Sorin
22. Repeated Games and Reputations. Mailath and Samuelson
23. Readings in Games and Information. Rasmusen
    

Bounded Rationality:

1. Modeling Bounded Rationality. Ariel Rubinstein
2. Rationality, Bounded Rationality and Microfoundations. Reza Salehnejad
3. Economics, Bounded Rationality and the Cognitive Revolution. Herbert Simon et al.

Microeconomics:

1. Auction Theory. Vijay Krishna
2. A Mathematical Approach to Economic Analysis. Peter Toumanoff and Farrokh Nourzad
3. Essential Mathematics for Economic Analysis. Knut Sydsater and Peter Hammond
4. Lecture Notes in Microeconomic Theory: The Economic Agent. Ariel Rubinstein

Greatest Evil

Inconsistency: switching between topics at the surface-level. The reason is fear, fear of losing even what might have been easy to achieve. Be pragmatic and be imaginative at the same time. One line is for career and the other is for the soul, for dreaming.

1. Stick to Game Theory as the creative line.

2. Stick to Usable Security, Location Privacy, and People-centric Sensing as the paper-generating lines.

3. Learn mobile phone programming as much as possible by doing projects.

1a. Learn Microeconomic Theory

2a. Read papers, generate ideas, imagine, and think, collaborate

3a. Meet every deadline cleanly for the Breast Cancer Project.

Lectures on Game Thery

• Links to Lecture Notes
• Polak's video lectures
  

Concave and Quasi-concave Functions

• A mathy introduction by Wilson
• Quasiconcavity and Quasiconvexity by Osborne

Textbooks...

I bought Playing For Real, a book on Game Theory by Ken Binmore. It was too wordy for me as a beginner and I became restless after a while, and the extensive use of Philosophical, Economic, and Card Games (I don't know Card Games) examples exacerbated my frustration. I found some suggested readings by Kevin Leyton-Brown in his website, he is the co-author of Essentials of Game Theory (EoGT). I started reading EoGT, but it was too concise for me. According to Kevin's suggestion (from his website), I have started reading, A Course in Game Theory by Martin J. Osborne and Ariel Rubinstein, today.

The beginning...

I was searching for some topic to pursue as a researcher. I had always been interested in consmogeny, abiogenesis, consciousness, and epsitemology. Each one is fundamental as well as big idea. Having been thrown into the realm of small devices, I started thinking, if the small device needs an entirely new from of intelligence. I came across the idea of Swarm Intelligence, which deals with the emergence of intelligent behavior out of simple actions and interactions among a huge number of almost dumb agents, e.g., a colony of ants (in contrast to Chaos Theory which investigates how simple initial rules can result in chaotic behavior). Small devices can be made smarter so that they are not so dumb as to work exclusively under the rubric of Swarm Intelligence. At the same time, they are resource-constrained in comparison to computers. Intelligent behavior calls for decision-making which leads us to Game Theory. Game Theory assumes that agents are rational and think strategically (in the shoes of others). Traditional Game Theory takes for granted that all agents in a game are equally rational, but in real life that is not the case most of the times. Also, in the digital world, there are diverse devices with different levels of analytical abilities due to resource-limitations which take part in games with one another. How to incorporate asymmetric rationality in agents in games? There is the Bounded Rationality, started by Herbert Simon which puts forth the idea of limitedly rational agents under resource-constraints. There have been some works in injecting limits or asymmetry in the agents' rationality in games. My motivation for openning this blog is to record my thoughts as I explore, learn, and discover ideas related to Game Theory in general, and in particular, Games played by agents with limited or asymmetric rationality. My plan is to see how I go along over a period of one year (till 6 July 2011).