My published benchmark for a Kaggle Simulations Competition

Related tags

Deep Learningkaggleartificial-intelligence
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

Erdene-Ochir Tuguldur 22 Nov 30, 2022
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

Kohei Ozaki 18 Aug 19, 2022
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

Erdene-Ochir Tuguldur 276 Dec 20, 2022
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

null 12 Oct 25, 2022
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

Rishit Dagli 54 Nov 1, 2022
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

Tarin Ziyaee 92 Sep 28, 2021
Kaggle G2Net Gravitational Wave Detection : 2nd place solution

Kaggle G2Net Gravitational Wave Detection : 2nd place solution

Hiroshechka Y 33 Dec 26, 2022
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

Jirka Borovec 9 Aug 12, 2022
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

Lingyuan Zhang 6 Mar 24, 2022
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 Repository https://kaggle.com/c/lux-ai-2021/
Code Release for ICCV 2021 (oral), "AdaFit: Rethinking Learning-based Normal Estimation on Point Clouds"

AdaFit: Rethinking Learning-based Normal Estimation on Point Clouds (ICCV 2021 oral) **Project Page | Arxiv ** Runsong Zhu¹, Yuan Liu², Zhen Dong¹, Te

40 Dec 30, 2022
Anomaly detection analysis and labeling tool, specifically for multiple time series (one time series per category)

taganomaly Anomaly detection labeling tool, specifically for multiple time series (one time series per category). Taganomaly is a tool for creating la

Microsoft 272 Dec 17, 2022
Official code for paper "Optimization for Oriented Object Detection via Representation Invariance Loss".

Optimization for Oriented Object Detection via Representation Invariance Loss By Qi Ming, Zhiqiang Zhou, Lingjuan Miao, Xue Yang, and Yunpeng Dong. Th

ming71 56 Nov 28, 2022
RRL: Resnet as representation for Reinforcement Learning

Resnet as representation for Reinforcement Learning (RRL) is a simple yet effective approach for training behaviors directly from visual inputs. We demonstrate that features learned by standard image

Meta Research 21 Dec 07, 2022
HDMapNet: A Local Semantic Map Learning and Evaluation Framework

HDMapNet_devkit Devkit for HDMapNet. HDMapNet: A Local Semantic Map Learning and Evaluation Framework Qi Li, Yue Wang, Yilun Wang, Hang Zhao [Paper] [

Tsinghua MARS Lab 421 Jan 04, 2023
EEGEyeNet is benchmark to evaluate ET prediction based on EEG measurements with an increasing level of difficulty

Introduction EEGEyeNet EEGEyeNet is a benchmark to evaluate ET prediction based on EEG measurements with an increasing level of difficulty. Overview T

Ard Kastrati 23 Dec 22, 2022
Implementation of ECCV20 paper: the devil is in classification: a simple framework for long-tail object detection and instance segmentation

Implementation of our ECCV 2020 paper The Devil is in Classification: A Simple Framework for Long-tail Instance Segmentation This repo contains code o

twang 98 Sep 17, 2022
Unsupervised Learning of Multi-Frame Optical Flow with Occlusions

This is a Pytorch implementation of Janai, J., Güney, F., Ranjan, A., Black, M. and Geiger, A., Unsupervised Learning of Multi-Frame Optical Flow with

Anurag Ranjan 110 Nov 02, 2022
Implementation of ICCV 2021 oral paper -- A Novel Self-Supervised Learning for Gaussian Mixture Model

SS-GMM Implementation of ICCV 2021 oral paper -- Self-Supervised Image Prior Learning with GMM from a Single Noisy Image with supplementary material R

HUST-The Tan Lab 4 Dec 05, 2022
Noether Networks: meta-learning useful conserved quantities

Noether Networks: meta-learning useful conserved quantities This repository contains the code necessary to reproduce experiments from "Noether Network

Dylan Doblar 33 Nov 23, 2022
Code for the prototype tool in our paper "CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning".

CoProtector Code for the prototype tool in our paper "CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning".

Zhensu Sun 1 Oct 26, 2021
[peer review] An Arbitrary Scale Super-Resolution Approach for 3D MR Images using Implicit Neural Representation

ArSSR This repository is the pytorch implementation of our manuscript "An Arbitrary Scale Super-Resolution Approach for 3-Dimensional Magnetic Resonan

Qing Wu 19 Dec 12, 2022
Official PyTorch(Geometric) implementation of DPGNN(DPGCN) in "Distance-wise Prototypical Graph Neural Network for Node Imbalance Classification"

DPGNN This repository is an official PyTorch(Geometric) implementation of DPGNN(DPGCN) in "Distance-wise Prototypical Graph Neural Network for Node Im

Yu Wang (Jack) 18 Oct 12, 2022
Attack on Confidence Estimation algorithm from the paper "Disrupting Deep Uncertainty Estimation Without Harming Accuracy"

Attack on Confidence Estimation (ACE) This repository is the official implementation of "Disrupting Deep Uncertainty Estimation Without Harming Accura

3 Mar 30, 2022
Synthesizing and manipulating 2048x1024 images with conditional GANs

pix2pixHD Project | Youtube | Paper Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic image-to-image translatio

NVIDIA Corporation 6k Dec 27, 2022
SuperSDR: multiplatform KiwiSDR + CAT transceiver integrator

SuperSDR SuperSDR integrates a realtime spectrum waterfall and audio receive from any KiwiSDR around the world, together with a local (or remote) cont

Marco Cogoni 30 Nov 29, 2022
Code for the CVPR2021 workshop paper "Noise Conditional Flow Model for Learning the Super-Resolution Space"

NCSR: Noise Conditional Flow Model for Learning the Super-Resolution Space Official NCSR training PyTorch Code for the CVPR2021 workshop paper "Noise

57 Oct 03, 2022
The official repository for our paper "The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers". We significantly improve the systematic generalization of transformer models on a variety of datasets using simple tricks and careful considerations.

Codebase for training transformers on systematic generalization datasets. The official repository for our EMNLP 2021 paper The Devil is in the Detail:

Csordás Róbert 57 Nov 21, 2022
An example project demonstrating how the Autonomous Learning Library can be used to build new reinforcement learning agents.

About This repository shows how Autonomous Learning Library can be used to build new reinforcement learning agents. In particular, it contains a model

Chris Nota 5 Aug 30, 2022
Sequence to Sequence Models with PyTorch

Sequence to Sequence models with PyTorch This repository contains implementations of Sequence to Sequence (Seq2Seq) models in PyTorch At present it ha

Sandeep Subramanian 708 Dec 19, 2022