Terminal Live, a game-based coding competition

 Algorithm coding battle sounds cool. That is the main reason why I chose to join the terminal competition, organized by Correlation One and Citadel, recommended by one of my friends Xinyu. It was the first time for me to take part in such a coding competition. Beyond my expectation, our team hit top 8 out of 34 participating teams. Special thanks to Henry Rossiter and Prajval Gupta, who are excellent team members to work with.

Made it to Finalist Bracket. Please forgive the organizers’ typo of our algo name.

Prajval made a thorough after-game analysis of pros and cons of our algorithms. Appreciate his summary here. Overall, we implemented a balanced strategy of defeating and defending, which performs well in the first several battles. Also, we chose to send waves of attackers every 3 turns with both “attack absorbers” and “tanks”. As the costs for different attack units were changed a lot specifically for the competition by the organizer, defending wave hit strategy somehow became difficult.

However, when encountered with opponents with super-long-wait-and-one-hit strategy, the defenses are barely strong enough. Our algo did not make it to help us win the award anyhow.

Here below is the video of the final competition of the top 2 teams. It wasn’t expected to have such a short final game as we watched a bunch of splendid long games including the one when we were defeated by Approx-Optimal. Seems like the defeated side in the final competition wasn’t able to build adequate defenses early enough to avoid the opponent’s wave hits.

https://youtu.be/wE7fBfTM4pk

Though it was impractical to implement fancy tools such as ML, RL, Q-learning, etc due to the time limit, this was still a pretty exciting coding game overall. Liked it.

Comments

Post a Comment

Popular posts from this blog

Lab Software Development 3 - Scanning Probe Microscope Controller

Image
Motivation     For home-build scanning probe systems in labs, SpecsGroup's Nanonis system is often considered a good solution with various working modes for piezo stage control. However, its' price may not be very friendly for some SPM systems, which do not need a sophisticated feedback PID loop. It is overkill especially for the non-feedback laser microwave impedance microscopy system in our lab. We had a LabView program developed by former students, but it lacks the rotational degree of freedom and line scan mode. Also, the UI's inconvenience has always been painful for users. In order to add more flexibility, I rebuilt a new control system for the SPM with QtCreator with Python as the backend. Functionalities     For convenience, all functionalities are embedded on the same page. Multithreading was implemented for scanning, imaging, and data saving. Many of the functionalities are following the workflow of Park AFM system.      Scan: By clicking "Scan", the con
Read more

Digit sequence detection of SVHN dataset

Image
  Unlike single digit detection problem like MNIST, images in SVHN dataset have more than one digit in series. SVHN Samples. Ref: http://ufldl.stanford.edu/housenumbers/ In this project, we used MSER detection and modified pre-trained VGG16 convolutional neural network to predict the digit sequence given a random image in SVHN dataset. Besides VGG16, we also used non-pre-trained VGG16 and self-built a much smaller CNN as comparisons. VGG16 Architecture. Ref: https://neurohive.io/en/popular-networks/vgg16/  Self-built CNN  The pipeline of the prediction is as: MSER detect blob regions →  CNN  find ROIs(regions of interest) → Combine overlapped/near ROIs →  CNN  Find Digits For training purposes, we mark each image with five integers as the label. The first four integers represent digits in the image, with 0 as no digit for that position and 1-10 representing 1-9 and 0. The fifth integer represents whether the area has any digit, with 0 represent a non-digit area and 1 as a window with d
Read more

Lab Software Development 2 - free-carrier DIFFUSION analysis system

Image
Quick screenshot: Paper using the software: https://www.nature.com/articles/s41467-021-25311-1 Motivation: This is a much more challenging project than the free-carrier lifetime analysis system even though this one does not include hardware control or communication. The free carrier diffusion measurement was already established and is running well. However, it is always very troublesome to do the diffusion length extractions, as our tools require three major fittings - signal response curve fitting, laser profile fitting, and convoluted Gaussian diffusion fitting. It is not possible to find a convenient commercial tool in the market to do the analysis, and it was very time-consuming to do manual analysis with Origin, Python, and other tools. A GUI would be much more convenient to use and can without a double boost the working efficiency of the lab. Environment: Since there is no control system needed, there is no need to use the lab-oriented tool LabView. Instead, I chose QtCreator and
Read more