https://github.com/cair/deep-line-wars

https://github.com/cair/deep-line-wars

Science Score: 13.0%

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    Low similarity (9.1%) to scientific vocabulary

Keywords

ai artificial-intelligence cpp deep-learning deep-reinforcement-learning game machine-learning neural-networks per-arne python reinforcement-learning reinforcement-learning-environments tree-search
Last synced: 5 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: cair
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 889 KB
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  • Stars: 1
  • Watchers: 3
  • Forks: 1
  • Open Issues: 1
  • Releases: 0
Topics
ai artificial-intelligence cpp deep-learning deep-reinforcement-learning game machine-learning neural-networks per-arne python reinforcement-learning reinforcement-learning-environments tree-search
Created almost 9 years ago · Last pushed almost 4 years ago
Metadata Files
Readme

README.md

DeepLineWars v1.0

DeepLIneWars is a real time strategy simulator which takes inspiration from Hero Line Wars, a Warcraft 3 mod available at battle.net

Purpose of this simulator is to use reinforcement learning to achieve perfect play.

Installation

bash pip3 install git+https://github.com/CAIR/DeepLineWars.git

Usage

Remember that non image representation is channels_first! ```python import gym import DeepLineWars # This is required in order to load DeepLineWars import os

if name == 'main':

# Reset environment
env = gym.make("deeplinewars-deterministic-11x11-v0")
s = env.reset()

# Set terminal state to false
terminal = False

while not terminal:
    # Draw environment on screen
    env.render()  # For image you MUST call this

    # Draw action from distribution
    a = env.action_space.sample()

    # Perform action in environment
    s1, r, t, _ = env.step(a)
    terminal = t

    s = s1

```

Environments

There are several environments available for Deep Line Wars deeplinewars-deterministic-11x11-v0 deeplinewars-deterministic-13x13-v0 deeplinewars-deterministic-15x15-v0 deeplinewars-deterministic-17x17-v0 deeplinewars-random-v0 deeplinewars-shuffle-11x11-v0 deeplinewars-shuffle-13x13-v0 deeplinewars-shuffle-15x15-v0 deeplinewars-shuffle-17x17-v0 deeplinewars-stochastic-11x11-v0 deeplinewars-stochastic-13x13-v0 deeplinewars-stochastic-15x15-v0 deeplinewars-stochastic-17x17-v0

Licence

Copyright 2017 Per-Arne Andersen

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Owner

  • Name: Centre for Artificial Intelligence Research (CAIR)
  • Login: cair
  • Kind: organization
  • Email: cair-internal@uia.no
  • Location: Grimstad, Norway

CAIR is a centre for research excellence on artificial intelligence at the University of Agder. We attack unsolved problems, seeking superintelligence.

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Dependencies

requirements.txt pypi
  • gym *
  • numpy *
  • opencv-python *
  • pygame *