ultimate-volleyball
TotalWarSimulator
| ultimate-volleyball | TotalWarSimulator | |
|---|---|---|
| 13 | 2 | |
| 84 | 57 | |
| - | - | |
| 0.0 | 0.0 | |
| about 2 years ago | almost 2 years ago | |
| C# | C# | |
| Apache License 2.0 | MIT License |
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ultimate-volleyball
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Volleyball agents trained using competitive self-play [tutorial + project link]
As linked in the tutorial, a Unity ML environment: https://github.com/CoderOneHQ/ultimate-volleyball
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Competitive self-play with Unity ML-Agents
The latest version of the Ultimate Volleyball repo (or, you can use your own volleyball environment if you've been following the tutorial series)
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Show HN: Bomberland – An AI competition to build the best Bomberman bot
No others (at the moment). We're a small team so Bomberland is our current focus - we want to improve the tooling first so that it's easy for people to dive into ML before we introduce other environments.
We do have a mini-project called Ultimate Volleyball (https://github.com/CoderOneHQ/ultimate-volleyball) built on Unity ML-Agents. It's intended more as an introduction to deep reinforcement learning, and we wrote some tutorials for it here if anyone's interested: https://www.gocoder.one/blog/hands-on-introduction-to-deep-r...
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How to train agents to play volleyball using deep reinforcement learning
Ultimate Volleyball Repo
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Design reinforcement learning agents using Unity ML-Agents
If you get stuck, check out the pre-configured BlueAgent , or see the full source code in the Ultimate Volleyball project repo.
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Bomberland: a 2D multi-agent environment for AI agents based on Bomberman
We're launching an upcoming project called Coder One where you can build agents to compete in a 2D game based on Bomberman.
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A multi-agent artificial intelligence playground [Looking for feedback]
If you're interested in checking it out, this is the website: https://www.gocoder.one
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A hands-on introduction to deep reinforcement learning using Unity ML-Agents
In this series, I'll walk you through how to use Unity ML-Agents to build a volleyball environment and train agents to play in it using deep RL. For a bit of fun and extra incentive, you'll be able to submit your trained agent to the Ultimate Volleyball leaderboard and have it compete against other agents.
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Last week fluff-free AI, ML, and data-related original articles summary
- Elon Musk unveils Tesla Bot, a humanoid robot that uses vehicle AI read - Multi-agent reinforcement learning environment built on Unity ML-Agents link read - Up to 40% of GitHub Copilot's generated code can be vulnerable read
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[P] A 3D Volleyball reinforcement learning environment built with Unity ML-Agents
Project: Link
TotalWarSimulator
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Who can watch this and still think it makes sense to spend another $60 on Total Warhammer III? It showcases everything from the absurdity of single model units to the complete lack of tactics or formations on the part of the AI.
GitHub - MichelangeloConserva/TotalWarSimulator: Total War Battle simulator for AI research
- Build It Ourselves
What are some alternatives?
ml-agents - The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
RoboLeague - A car soccer environment inspired by Rocket League for deep reinforcement learning experiments in an adversarial self-play setting.
bomberland - Bomberland: a multi-agent AI competition based on Bomberman. This repository contains both starter / hello world kits + the engine source code
SS3D - Space Station 3D, another remake of SS13, but with an extra D.
ultimate-volleyball-starter - Tutorial kit for building a 3D deep reinforcement learning environment with Unity ML-Agents.
simulator - A ROS/ROS2 Multi-robot Simulator for Autonomous Vehicles
minimalRL - Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
ZeroSimROSUnity - Robotic simulation in Unity with ROS integration.
SimpleGOAP - SimpleGOAP is a lightweight C# implementation of goal oriented action planning.