|14 days ago||about 1 year ago|
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Show HN: Bomberland – An AI competition to build the best Bomberman bot
4 projects | news.ycombinator.com | 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: https://github.com/CoderOneHQ/bomberland 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: https://discord.gg/NkfgvRN
Bomberland: a new artificial intelligence competition
1 project | dev.to | 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).
1 project | reddit.com/r/reinforcementlearning | 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](https://github.com/thomashirtz/q-learning-algorithms). 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?
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