bomberland VS q-learning-algorithms

Compare bomberland vs q-learning-algorithms and see what are their differences.


Bomberland: a multi-agent AI competition based on Bomberman. This repository contains both starter / hello world kits + the engine source code (by CoderOneHQ)


This repository will aim to provide implementations of q-learning algorithms (DQN, Double-DQN, ...) using Pytorch. (by thomashirtz)
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bomberland q-learning-algorithms
2 1
61 3
- -
6.8 0.0
14 days ago about 1 year ago
C++ Python
MIT License -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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Posts with mentions or reviews of bomberland. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-24.
  • Show HN: Bomberland – An AI competition to build the best Bomberman bot
    4 projects | | 24 Sep 2021
    Thanks for the feedback! We're working on improving the onboarding flow. Sorry about the Docker link issue - it should link you to a copy of the environment binary so that you can play around without Docker (no docs for this workflow just yet unfortunately).

    It's essentially a Bomberman-inspired game, where you program the agents to play in it and can play against other users' agents. You can try it out without an account by cloning one of the starter kits here: and following the usage instructions (but you'll need to create an account to use the visualizer and to submit agents).

    We recommend the Docker flow, but if you get stuck feel free to reach out to me (Joy) or @thegalah (Matt) on our Discord:

  • Bomberland: a new artificial intelligence competition
    1 project | | 19 Sep 2021
    We have starter kits in Python and TypeScript to help you get started (and encourage any community contributions to the starter kit repo).


Posts with mentions or reviews of q-learning-algorithms. We have used some of these posts to build our list of alternatives and similar projects.
  • actor-critic algorithms
    1 project | | 11 Apr 2021
    I learn quite some things about reinforcement learning in the last months, and I feel like I understand much better deep-Q learning algorithms (if you want, you can check my [repo]( I would like to change a little bit my focus towards actor-critics algorithms now. The only thing is, I feel like in comparison to Q-learning algorithms, the explanations of the papers are not as precise as for Q-learning, and explanations on the internet diverge really greatly (e.g. the original paper does not give the A2C but only the A3C for one learner).

What are some alternatives?

When comparing bomberland and q-learning-algorithms you can also consider the following projects:

chess - Program for playing chess in the console against AI or human opponents

ultimate-volleyball - 3D RL Volleyball environment built on Unity ML-Agents

control-flag - A system to flag anomalous source code expressions by learning typical expressions from training data