Genetic algorithm which evolves aoe2 DE ai scripts

Overview

AlphaScripter

Use the power of genetic algorithms to evolve AI scripts for Age of Empires II : Definitive Edition. For now this package runs in AOC Userpatch 1.5 to train. In theory, scripts generated this way should be compatible with Age of Empires II : Definitive Edition, but in practice a certain amount of porting will need to take place. This is currently a work in progress.

Dependencies

  • msgpackrpc >= 0.4.1 : A package used to communicate with running AOE processes. (To install, pip install msppack-rpc-python)
  • psutil >= 5.8.0 : A package used to manage running processes.
  • tornado == 4.3.5 : Should be automatically installed with msgpackrpc.

How to install and run

  1. Install 32-bit (!) Python (tested with version 3.9) and the dependencies listed above.
  2. Install Age of Empires II - The Conquerors and install UserPatch 1.5. The UserPatch can be found here: https://userpatch.aiscripters.net/
  3. Download the aoc-auto-game.dll and paste it in the same folder as the AOC executable. You can download this DLL file here.
  4. Open the Python file Main.py, adjust parameters and run the script. (WIP)

What does it do? - Explanation per script

The Main Script Main.py

On run, the script will generate an AI named "Alpha," load it into a game versus the training ai (Alpha must be in the second slot). The script will automatically start new games from the post game menu -- you may want to speed up the game in the first round, and/or end the first round early as it won't count for scoring.

Your game may crash. If it does, you can pause the script with control-v and reset. It will save the progress.

The best script so far will be saved as "best.per" in the .ai directory. It will be overwritten if you restart the script.

The png files are necessary for the auto-load new game function.

I will expand this later -- if you would like to help with this project, you can find me on the AI scripters discord for aoe2 de and dm me. I specifically need help from those knowledgeable about scripting or engine modification.

Run types: You can run vs, run score, or run FFA.

run vs: load alpha into p1 and beta into p2. Game will pick winner as new parent - this is a good adversarial AI but is best for late stage training once the AI is good enough to possibly defeat another player

run score: load training AI (HD, barbarian, extreme) into p1 and alpha into p2 Game will pick all-time-highest scorers as new parent.

run FFA: load alpha-h into slots 1-8, make sure no teams are selected Game will pick two best in each round and crossover their traits. Very good for fast training early on.

Game Launcher game_launcher.py

The game launcher is used to, surprise, launch games. To successfully launch a game, the class Launcher needs to be instantiated. This will take 1 optional argument: path that specifies the path to the AOC executable. If you don't pass this argument, the game will look for the executable in the default path: C:\Program Files\Microsoft Games\age of empires ii\Age2_x1\age2_x1.exe. If the executable cannot be found, the launcher will raise an Exception.

After correctly instantiating this Launcher, you can launch a game using the Launcher.launch_game function. This function takes 2 required and 3 optional arguments:

  • (Required) names : list[str] - This is a list of strings that represent the names of the AI .per files that the game will look for when starting the game. These should be in the ..\age of empires ii\ai folder.
  • (Required) game_settings - This should be an instance of the GameSettings class, which is also declared in game_launcher.py.
  • (Optional) real_time_limit : int - The number of real time seconds after which the game(s) should be automatically quit and closed. If not given, there will not be a real-time limit.
  • (Optional) game_time_limit : int - The number of in-game seconds after the game(s) should be quit and closed.
  • (Optional) instances : int - The number of games to run simultaneously. This currently a little experimental, so keep in mind that your mileage with this setting.

The GameSettings class is used to store settings for the game. To instantiate a GameSettings object, you will have to pass 1 required argument and a lot of optional arguments. See below for a description.

  • (Required) civilisations - A list of strings or int (can also be mixed) that represent the civs that the AI players will use. It must be the same length as the names given to the launcher, otherwise the launcher will raise an Exception. If an element in the given list is not a valid civ, that element will be replaced by 'huns'.
  • (Optional) map_id - A string or int that represents the map. Default 'arabia'
  • (Optional) map_size - A string or int that represent the map size. Default 'medium'
  • (Optional) difficulty - A string or int that represents the difficulty of the game. Default 'hard'
  • (Optional) game_type - Specifies the game type. Default 'random_map'
  • (Optional) resources - Specifies the starting resources of each player. Default 'low'
  • (Optional) reveal_map - Whether the map should be revealed. Default 'normal'
  • (Optional) starting_age - Which age the players should start in. Default 'dark'
  • (Optional) victory_type - The victory type. Doesn't work (yet). Default 'conquest'
It is a platform that implements some path planning algorithms.

PathPlanningAlgorithms It is a platform that implements some path planning algorithms. Main dependence: python3.7, opencv4.1.1.26 (for image show) Tip

5 Feb 24, 2022
Our implementation of Gillespie's Stochastic Simulation Algorithm (SSA)

SSA Our implementation of Gillespie's Stochastic Simulation Algorithm (SSA) Requirements python =3.7 numpy pandas matplotlib pyyaml Command line usag

Anoop Lab 1 Jan 27, 2022
A Python project for optimizing the 8 Queens Puzzle using the Genetic Algorithm implemented in PyGAD.

8QueensGenetic A Python project for optimizing the 8 Queens Puzzle using the Genetic Algorithm implemented in PyGAD. The project uses the Kivy cross-p

Ahmed Gad 16 Nov 13, 2022
Tic-tac-toe with minmax algorithm.

Tic-tac-toe Tic-tac-toe game with minmax algorithm which is a research algorithm his objective is to find the best move to play by going through all t

5 Jan 27, 2022
This repository explores an implementation of Grover's Algorithm for knights on a chessboard.

Grover Knights Welcome to my Knights project! Project Description: I explore an implementation of a quantum oracle for knights on a chessboard.

Will Sun 8 Feb 22, 2022
A Python Package for Portfolio Optimization using the Critical Line Algorithm

A Python Package for Portfolio Optimization using the Critical Line Algorithm

19 Oct 11, 2022
An open source algorithm and dataset for finding poop in pictures.

The shitspotter module is where I will be work on the "shitspotter" poop-detection algorithm and dataset. The primary goal of this work is to allow for the creation of a phone app that finds where yo

Jon Crall 29 Nov 29, 2022
zoofs is a Python library for performing feature selection using an variety of nature inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics based to Evolutionary. It's easy to use ,flexible and powerful tool to reduce your feature size.

zoofs is a Python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's e

Jaswinder Singh 168 Dec 30, 2022
Given a list of tickers, this algorithm generates a recommended portfolio for high-risk investors.

RiskyPortfolioGenerator Given a list of tickers, this algorithm generates a recommended portfolio for high-risk investors. Working in a group, we crea

Victoria Zhao 2 Jan 13, 2022
Distributed Grid Descent: an algorithm for hyperparameter tuning guided by Bayesian inference, designed to run on multiple processes and potentially many machines with no central point of control

Distributed Grid Descent: an algorithm for hyperparameter tuning guided by Bayesian inference, designed to run on multiple processes and potentially many machines with no central point of control.

Martin 1 Jan 01, 2022
QDax is a tool to accelerate Quality-Diveristy (QD) algorithms through hardware accelerators and massive parallelism

QDax: Accelerated Quality-Diversity QDax is a tool to accelerate Quality-Diveristy (QD) algorithms through hardware accelerators and massive paralleli

Adaptive and Intelligent Robotics Lab 183 Dec 30, 2022
Data Model built using Logistic Regression Algorithm on Python.

Logistic-Regression Problem Statement: Your client is a retail banking institution. Term deposits are a major source of income for a bank. A term depo

Hemanth Babu Muthineni 0 Dec 25, 2021
Implementation of core NuPIC algorithms in C++

NuPIC Core This repository contains the C++ source code for the Numenta Platform for Intelligent Computing (NuPIC)

Numenta 270 Nov 19, 2022
Cormen-Lib - An academic tool for data structures and algorithms courses

The Cormen-lib module is an insular data structures and algorithms library based on the Thomas H. Cormen's Introduction to Algorithms Third Edition. This library was made specifically for administeri

Cormen Lib 12 Aug 18, 2022
Implementation for Evolution of Strategies for Cooperation

Moraliser Implementation for Evolution of Strategies for Cooperation Dependencies You will need a python3 (= 3.8) environment to run the code. Before

1 Dec 21, 2021
Evol is clear dsl for composable evolutionary algorithms that optimised for joy.

Evol is clear dsl for composable evolutionary algorithms that optimised for joy. Installation We currently support python3.6 and python3.7 and you can

GoDataDriven 178 Dec 27, 2022
Official implementation of "Path Planning using Neural A* Search" (ICML-21)

Path Planning using Neural A* Search (ICML 2021) This is a repository for the following paper: Ryo Yonetani*, Tatsunori Taniai*, Mohammadamin Barekata

OMRON SINIC X 82 Jan 07, 2023
Algorithms and data structures for educational, demonstrational and experimental purposes.

Algorithms and Data Structures (ands) Introduction This project was created for personal use mostly while studying for an exam (starting in the month

50 Dec 06, 2022
Nature-inspired algorithms are a very popular tool for solving optimization problems.

Nature-inspired algorithms are a very popular tool for solving optimization problems. Numerous variants of nature-inspired algorithms have been develo

NiaOrg 215 Dec 28, 2022