My published benchmark for a Kaggle Simulations Competition

Overview

Lux AI Working Title Bot

Please refer to the Kaggle notebook for the comment section. The comment section contains my explanation on my code structure and logic.

This README will explain how to use this repository.

Setup

Run ./setup.sh to install the required components.

Make submission files

Run ./make_submit.sh to generate the following files

  • The zipfile submission.tar.gz which can be submitted to Kaggle directly.
  • The notebook submission notebook_generated.ipynb. You can upload this notebook into a fork of my notebook and submit.

Running a Game

You can run a game with notebook_test.ipynb

game-rerun-screenshot

You may define the width and height of the board, as well as the seed. Annotations are shown on the board.

This code snippet is also run in the generated notebook.

Analysing Game State and Missions

You may run the game logic on a specific turn with notebook_debug.ipynb to understand why the agent made a certain decision.

debug-screenshot

When the run is made with notebook_test.ipynb, the game state, and missions are saved as Python pickle files. You may load the Python pickle file and run the game logic to produce the actions and updated missions.

As the game logic is run, it prints the new mission planned, the actions made include the annotation.

You can modify the code and see how the agent reacts different for the same game state and missions. This allows you iteratively improve the agent more quicking.

This code snippet is also run in the generated notebook.

You might also like...
Kaggle | 9th place (part of) solution for the Bristol-Myers Squibb – Molecular Translation challenge

Part of the 9th place solution for the Bristol-Myers Squibb – Molecular Translation challenge translating images containing chemical structures into I

My 1st place solution at Kaggle Hotel-ID 2021

1st place solution at Kaggle Hotel-ID My 1st place solution at Kaggle Hotel-ID to Combat Human Trafficking 2021. https://www.kaggle.com/c/hotel-id-202

Kaggle | 9th place single model solution for TGS Salt Identification Challenge

UNet for segmenting salt deposits from seismic images with PyTorch. General We, tugstugi and xuyuan, have participated in the Kaggle competition TGS S

10th place solution for Google Smartphone Decimeter Challenge at kaggle.
10th place solution for Google Smartphone Decimeter Challenge at kaggle.

Under refactoring 10th place solution for Google Smartphone Decimeter Challenge at kaggle. Google Smartphone Decimeter Challenge Global Navigation Sat

Monitor your ML jobs on mobile devices📱, especially for Google Colab / Kaggle
Monitor your ML jobs on mobile devices📱, especially for Google Colab / Kaggle

TF Watcher TF Watcher is a simple to use Python package and web app which allows you to monitor 👀 your Machine Learning training or testing process o

A whale detector design for the Kaggle whale-detector challenge!
A whale detector design for the Kaggle whale-detector challenge!

CNN (InceptionV1) + STFT based Whale Detection Algorithm So, this repository is my PyTorch solution for the Kaggle whale-detection challenge. The obje

Kaggle G2Net Gravitational Wave Detection : 2nd place solution

Kaggle G2Net Gravitational Wave Detection : 2nd place solution

 Kaggle: Cell Instance Segmentation
Kaggle: Cell Instance Segmentation

Kaggle: Cell Instance Segmentation The goal of this challenge is to detect cells in microscope images. with simple view on how many cels have been ann

Kaggle Feedback Prize - Evaluating Student Writing 15th solution

Kaggle Feedback Prize - Evaluating Student Writing 15th solution First of all, I would like to thank the excellent notebooks and discussions from http

Comments
  • Maybe a bug.

    Maybe a bug.

    https://github.com/tonghuikang/lux-ai-2021/blob/86d06bb0ae799bd66f732052597fd67d2d91cbf0/lux/game.py#L447

    When reading your sharing code for lux-ai-2021, I found there may be a bug.

    In file game.py , the function calculate_distance_matrix() near line 447, I think it should be:

    x_distance_from_edge = min(x, self.map_width-x-1)
    

    Since we are calculating the distance from edge here, that's to say we need y-to-edge and x-to-edge.

    Maybe I am wrong and not get the key point.
    And thanks for your sharing : )

    opened by floudk 2
Releases(rules-final)
Owner
Tong Hui Kang
Redrawing Electoral Boundaries
Tong Hui Kang
Github project for Attention-guided Temporal Coherent Video Object Matting.

Attention-guided Temporal Coherent Video Object Matting This is the Github project for our paper Attention-guided Temporal Coherent Video Object Matti

71 Dec 19, 2022
LSSY量化交易系统

LSSY量化交易系统 该项目是本人3年来研究量化慢慢积累开发的一套系统,属于早期作品慢慢修改而来,仅供学习研究,回测分析,实盘交易部分未公开

55 Oct 04, 2022
Implementation of Graph Convolutional Networks in TensorFlow

Graph Convolutional Networks This is a TensorFlow implementation of Graph Convolutional Networks for the task of (semi-supervised) classification of n

Thomas Kipf 6.6k Dec 30, 2022
Code and description for my BSc Project, September 2021

BSc-Project Disclaimer: This repo consists of only the additional python scripts necessary to run the agent. To run the project on your own personal d

Matin Tavakoli 20 Jul 19, 2022
To prepare an image processing model to classify the type of disaster based on the image dataset

Disaster Classificiation using CNNs bunnysaini/Disaster-Classificiation Goal To prepare an image processing model to classify the type of disaster bas

Bunny Saini 1 Jan 24, 2022
Knowledge Distillation Toolbox for Semantic Segmentation

SegDistill: Toolbox for Knowledge Distillation on Semantic Segmentation Networks This repo contains the supported code and configuration files for Seg

9 Dec 12, 2022
Supplemental Code for "ImpressionNet :A Multi view Approach to Predict Socio Facial Impressions"

Supplemental Code for "ImpressionNet :A Multi view Approach to Predict Socio Facial Impressions" Environment requirement This code is based on Python

Rohan Kumar Gupta 1 Dec 19, 2021
Count the MACs / FLOPs of your PyTorch model.

THOP: PyTorch-OpCounter How to install pip install thop (now continously intergrated on Github actions) OR pip install --upgrade git+https://github.co

Ligeng Zhu 3.9k Dec 29, 2022
Bayesian optimisation library developped by Huawei Noah's Ark Library

Bayesian Optimisation Research This directory contains official implementations for Bayesian optimisation works developped by Huawei R&D, Noah's Ark L

HUAWEI Noah's Ark Lab 395 Dec 30, 2022
Sequence lineage information extracted from RKI sequence data repo

Pango lineage information for German SARS-CoV-2 sequences This repository contains a join of the metadata and pango lineage tables of all German SARS-

Cornelius Roemer 24 Oct 26, 2022
PyTorch implementation of Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation.

ALiBi PyTorch implementation of Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation. Quickstart Clone this reposit

Jake Tae 4 Jul 27, 2022
Atomistic Line Graph Neural Network

Table of Contents Introduction Installation Examples Pre-trained models Quick start using colab JARVIS-ALIGNN webapp Peformances on a few datasets Use

National Institute of Standards and Technology 91 Dec 30, 2022
This program uses trial auth token of Azure Cognitive Services to do speech synthesis for you.

🗣️ aspeak A simple text-to-speech client using azure TTS API(trial). 😆 TL;DR: This program uses trial auth token of Azure Cognitive Services to do s

Levi Zim 359 Jan 05, 2023
Losslandscapetaxonomy - Taxonomizing local versus global structure in neural network loss landscapes

Taxonomizing local versus global structure in neural network loss landscapes Int

Yaoqing Yang 8 Dec 30, 2022
Music Classification: Beyond Supervised Learning, Towards Real-world Applications

Music Classification: Beyond Supervised Learning, Towards Real-world Applications

104 Dec 15, 2022
Link prediction using Multiple Order Local Information (MOLI)

Understanding the network formation pattern for better link prediction Authors: [e

Wu Lab 0 Oct 18, 2021
My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs (GNN, GAT, GraphSAGE, GCN)

machine-learning-with-graphs My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs Course materials can be

Marko Njegomir 7 Dec 14, 2022
An implementation of the methods presented in Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data.

An implementation of the methods presented in Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data.

Andrew Jesson 9 Apr 04, 2022
Credit fraud detection in Python using a Jupyter Notebook

Credit-Fraud-Detection - Credit fraud detection in Python using a Jupyter Notebook , using three classification models (Random Forest, Gaussian Naive Bayes, Logistic Regression) from the sklearn libr

Ali Akram 4 Dec 28, 2021
Implementation for NeurIPS 2021 Submission: SparseFed

READ THIS FIRST This repo is an anonymized version of an existing repository of GitHub, for the AIStats 2021 submission: SparseFed: Mitigating Model P

2 Jun 15, 2022