Algorithmic Game Theory Lecture Videos and Notes

Link to Stanford professor, Tim Roughgarden’s video lectures on algorithmic game theory (AGT):

2013 Iteration
http://theory.stanford.edu/~tim/f13/f13.html

2014 Iteration
http://theory.stanford.edu/~tim/f14/f14.html

I’m currently doing his Coursera MOOC on algorithms, divided into 2 parts:

https://www.coursera.org/course/algo
https://www.coursera.org/course/algo2

Turing's Invisible Hand

I’m teaching my algorithmic game theory course at Stanford this quarter, and this time around I’m posting lecture videos and notes.  The videos are a static shot of my blackboard lectures, not MOOC-style videos.

The course home page is here.  Week 1 videos and notes, covering several motivating examples and some mechanism design basics, are already available.  This week (Week 2) we’ll prove the correspondence between monotone and implementable allocation rules in single-parameter environments, and introduce algorithmic mechanism design via Knapsack auctions.

The ten-week course has roughly four weeks of lectures on mechanism design, three weeks on the inefficiency of equilibria (e.g., the price of anarchy), and three weeks on algorithms for and the complexity of learning and computing equilibria. Periodically, I’ll post updates on the course content in this space.  I would be very happy to receive comments, corrections, and criticisms on the course organization and content.

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Visualizing Macroeconomic Data using Choropleths in R

Choropleths are thematic maps shaded or patterned in proportion to the measurement of the statistical variable being displayed on the map, such as population density or per-capita-income.

example choropleth

This post is about creating quick choropleth maps in R, with macroeconomic data across geographies.

As a sample exercise, I decided to get data on what percentage of their aggregate disbursements, do states in India spend on development expenditure. I got the data from the Reserve Bank of India’s website. I had to clean the data a little for easy handling in R. Here’s the cleaned data.

I used the choroplethr package designed by Ari Lamstein and Brian P Johnson to animate the data on the map of India. Here’s my code followed by output maps.

…and as expected, the lines of code above print out the desired map

Expenditure on Development in Southern States (2012)

In the examples above I set the buckets attribute equal to 9. That set the data in discrete scales. Had I set buckets = 1 instead, we would have got a continuous scale of data.

Expenditure on Development (2012)_continuous

The same for the last 2 fiscal years:

Development Expenditures in the Last 2 Years

For the US, there are amazing packages for county level and ZIP code level detail of data visualization.

Here’s more on the choroplethr package for R and creating your own maps.

Hello World!

Hello World

Hi all!

This website would be a most unusual way to blog about programming languages, that too coming from someone who hasn’t done much coding. In the next few minutes, I offer an introduction. It’s divided into 2 parts.

(i) introducing myself
(ii) an introduction to WHY I created this blog

Intro (i)

I am an electrical engineer who took to finance after graduating from college — doing what I’d like to think was preparing client pitches that bankers would use to wrap up multi-million dollar deals!

Just kidding. All I was doing was waiting for the last day of the month for the salary figure to pop up as a message in my phone’s inbox, i.e., watching my bank balance go up every month. It was in a moment of epiphany that I realized that I had better quit before I got used to being that way.

I then spent some time working as a social media analyst for a revolutionary political outfit — around the same time when the capital city of India was going to the polls for the Assembly elections. Politics sparked my curiosity for what was coming next – Economics!

I fell in love immediately, which found me studying economics here, at a research institute funded by the RBI, India’s equivalent of the Fed. I braved a semester, managing a face-saving GPA, for it had been 3 years since I had left academics, and I was moving to something unrelated to what I had been doing in the past, so the transition couldn’t have been smooth, I knew that.

Nevertheless, when I was taking my end of term exams that semester, it was after 2 weeks of hitting the gym. But life has its ways of throwing lemons at us from time to time. I’m now trying to squeeze the juice out of them for the proverbial lemonade. Anyway, I had to cut short my attempts at acquiring a six pack when it started to pain in my pelvic region, and my right leg had gone numb. Through the pain I somehow managed to appear for the end terms. When I was home after my exams, the pain gradually got worse and rose — like a crescendo!

Intro (ii)

Turns out I had what is commonly known as a slipped disc. I had herniations in L4-L5 and L5-S1 discs of my spine, with a 100% prolapse in the latter.

It’s been very painful. I can’t sit for more than 5 minutes without getting muscular spasms in my lumbar region, numbness in my feet and distressing nerve pain in my toes, buttocks and thighs that last for a couple of days each time I try sitting. Can’t stand longer than 10 minutes.

In summary, I’ve been bedridden for over 16 weeks now and have 9 months ahead of me before I can continue my education from where I had to leave it. Staying confined in a room for months on end, sick, is worse than being locked up in prison. It makes going to the doctor seem like a picnic!

I always wanted to get my hands dirty with programming, so I decided after much deliberation, that I would learn as much of Python and R as I can in the coming months. I’ll talk more about WHY, in some of my future posts (like this one), but for now it should suffice if I told you I want to keep myself from getting bored to death. For the months of April through December, this blog is meant to document my learning and struggles, insights and revelations.

What better way to start than this —

> print(“Hello World”)  # R
>>> print “Hello World”  # Python