Skip to main content

Package the Artificial Intelligence in Games and Simulation course

Project description

aigs

To get up and running:

  1. Install uv so you can get our environment up and running (https://docs.astral.sh/uv/)
  2. Clone this repo git clone https://github.com/syrkis/aigs.git

Open the repo in your IDE. You can run the code with our dependencies using uv run python

labs

  • MCTS. Find a simple game (easier than chess or go) that can be played in the temrinal.
    1. Implement the game (do it in unity if you want) (connect four or checkers)
    2. Impement MCTS
    3. play with params and have a competation
  • DRL (getting a good player)
    1. get unity ml-agent to run
    2. pick game. Use PPO. Finetune.
  • quality diversity (finding good levels)
    1. implement map elite for levels
    2. create a dataset of different solvable levels

exam

  1. Make your own game that is more awesome than default unity, and train ppo on it

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

aigs-0.1.0.tar.gz (2.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

aigs-0.1.0-py3-none-any.whl (3.4 kB view details)

Uploaded Python 3

File details

Details for the file aigs-0.1.0.tar.gz.

File metadata

  • Download URL: aigs-0.1.0.tar.gz
  • Upload date:
  • Size: 2.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.8.2

File hashes

Hashes for aigs-0.1.0.tar.gz
Algorithm Hash digest
SHA256 46baa530817b21d3af4c4bde430cb762e4f676ac6499d559b3804a7ac4131d9d
MD5 9d6ee2d2559d67e0b11aa2da1a3a21bb
BLAKE2b-256 1faf37415f660a2c8044dd421e4171d241c4b9d9cdc1053df3b40410d7bc62a8

See more details on using hashes here.

File details

Details for the file aigs-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: aigs-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 3.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.8.2

File hashes

Hashes for aigs-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 b76dc9bf6116dd41da6276e6eaa1726ec47098c3f45aad0fc358f5e621576f20
MD5 2e14b81712a00e62fd0954c309f3dc11
BLAKE2b-256 56cf2035e9d16fbe4b6992c5886cacbd3edff65b8dfe882a660fd8d8bd36800a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page