One of my quests during the research project I did last summer was to find a way to simulate pointers in Python, or at the very least, get some sort of named reference-like behaviour from the language. Unfortunately, I quickly learned that this is quasi-impossible, because Python is a language that aims to abstract as many implementation details away from the user as possible, and gives programmers very limited ways in which to interact with the language.

While all NP-hard optimization problems are identical in terms of exact solvability, they may differ wildly from the approximative point of view. If the goal is to obtain an answer that is “good enough”, some problems become much easier (such as KNAPSACK), while others (such as CLIQUE) remain extremely hard.

Here’s a look at some of the articles and books I’ve been reading lately, or at least, the ones that stuck out to me. Originally, I wanted to do this as a weekly series, inspired by Cory Doctorow’s link posts where he comments on various articles he’s read - but I don’t have that kind of time. Also, I’m really not that great at remembering the various articles I’ve stumbled through online, so you’re going to get these when you get them.