Imagine a shared resource, such as a compute server. Users can submit jobs to the server. The resource is “free”, in the sense that no costs are imposed on the users. The question is how to best assign and prioritize jobs when multiple users submit jobs simultaneously.
The (notorious) Dirac delta-function is usually introduced as a function with the following properties: \[ \delta(x) = \begin{cases} 0 & \qquad x \neq 0 \\ \text{“$\infty$”} & \qquad x = 0 \end{cases} \]
Over the holidays, I had the opportunity to work on a spare time project, and so I sat down and wrote a casual, turn-based strategy game; a variant (you might say: a clone) of the KDE game Konquest.
Finding a realistic (or at least, realistic looking) initial configuration of game objects or simulation particles can be a challenge. The desired configuration should appear to be both “random” and at the same time “spatially uniform”, without objects clustering together or overlapping.
I have started to get interested in Hidden Markov Models (HMM). As a warm-up, I prepared a pure Python implementation of the relevant algorithms (github).
This site is generated using Hugo. Getting the site up and running was nothing short of a nightmare, which I have documented elsewhere. But things are working now, and Hugo makes adding new content very easy indeed. It therefore seems a good opportunity to reflect back and revisit the whole “Static Site Generator” a.k.a. “JamStack” topic, from a greater distance.
The “Newsvendor Problem” is a classic problem in inventory and supply-chain management: how much product to carry in stock in the face of uncertain demand?
The problem is obviously of interest in its own right, but it is also an archetypical problem, meaning that variations of it arise frequently and in different contexts. It is therefore valuable to know “how to think about” this kind of problem; in particular, since in its simplest form, it has a closed-form, analytic solution.
In a moment of nostalgia, I picked up my copy of “The Art of UNIX Programming” by Eric S. Raymond (esr) and flipped through it again. It’s a book I’ve had since when it came out in 2004, and that I’ve always been quite fond of. I was looking forward to a review of “the way the future was”, as viewed from the early 2000s. So, it came as a bit of a surprise to me to find that the book seems to have aged rather poorly.
Processing command-line arguments in ad-hoc python tools is one of those areas where I tend to just hack it together from scratch — simply because the effort of learning and understanding the relevant library packages not only seems to be more work than it is worth, but also and in particular more effort than “just doing it” by hand. I don’t want anything fancy, after all. I just want to get it done.