Life & fun · alternatives · 2026

24 alternatives to Reinforcement Learning from Scratch with TypeScript

Reinforcement Learning (DQN) from scratch with zero dependencies applied to a simple car driving game - desi-ivanov/cars-rl

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Reinforcement Learning from Scratch with TypeScript launched in 2023; newer entries below may have overtaken it.

1
I RL-trained an agent that trains models with RL (for ~$1.3k)▲107
RL-training an AI agent to RL-train AI agents. Contribute to Danau5tin/ai-trains-ai development by creating an account on GitHub.
Jul 2026 · github.com · its alternatives →
2BP
Beating Pokemon Red with RL and <10M Parameters▲183
Hi everyone! After spending hundreds of hours, we're excited to finally share our progress in developing a reinforcement learning system to beat Pokémon Red. Our system successfully completes the game using a policy under 10M parameters, PPO, and a few novel techniques. With the release of Claude Plays Pokémon, now feels like the perfect time to showcase our work. We'd love to get feedback!
2025 · drubinstein.github.io · its alternatives →
3
Fast Deep Reinforcement Learning Course▲148
I worked on this applied Deep Reinforcement Learning course for the better part of 2021. I made a Datacamp course [0] before, and this served as my inspiration to make an applied Deep RL series. Normally, Deep RL courses teach a lot of mathematically involved theory. You get the practical applications near the end (if at all). I have tried to turn that on its head. In the top-down approach, you learn practical skills first, then go deeper later. This is much more fun. This course (the first in a planned multi-part series) shows how to use the Deep Reinforcement Learning framework RLlib to…
2022 · courses.dibya.online · its alternatives →
4HI
How I built a self-driving (RC) car.▲300
I have been taking Andrew Ng's Machine Learning course. The lecture module on Neural Networks ends with an intriguing video of the ALVINN autonomous car driving itself along normal roads at CMU in the mid 90s. I was inspired by that video to see what I could build myself. A link to my incomplete write up was posted a couple of weeks ago (ouch!) but I finally finished it and open sourced the code tonight (so you can build your own self driving car). What do you think? http://blog.davidsingleton.org/nnrccar https://github.com/dps/nnrccar
2012 · blog.davidsingleton.org · its alternatives →
5
ART – a new open-source RL framework for training agents▲116
Hey HN, I wanted to share a new project we've been working on for the last couple of months called ART (https://github.com/OpenPipe/ART). ART is a new open-source framework for training agents using reinforcement learning (RL). RL allows you to train an agent to perform better at any task whose outcome can be measured and quantified. There are many excellent projects focused on training LLMs with RL, such as GRPOTrainer (https://huggingface.co/docs/trl/main/en/grpo_trainer) and verl…
2025 · github.com · its alternatives →
6
A Simple Highway Simulator▲219
This little app is a simple simulator of cars on a highway. Play with the parameters or stop any car by touching it. Choose between two kind of AI engines
2016 · muehlemann.com · its alternatives →
7
Recurrent neural net plays 'neural slime volleyball' in JavaScript▲147
2015 · otoro.net · its alternatives →
8
LlamaGym – fine-tune LLM agents with online reinforcement learning▲239
Fine-tune LLM agents with online reinforcement learning - KhoomeiK/LlamaGym
2024 · github.com · its alternatives →
9
Next-Gen AI Training: LLM-RLHF-Tuning with PPO and DPO▲30
Comprehensive toolkit for Reinforcement Learning from Human Feedback (RLHF) training, featuring instruction fine-tuning, reward model training, and support for PPO and DPO algorithms with various configurations for the Transformer 5 models including Qwen 3.0 - raghavc/LLM-RLHF-Tuning-with-PPO-and-DP
2024 · github.com · its alternatives →
10
Quake 1 movement physics reinforcement learning project▲91
Quake 1 movement physics reinforcement learning. Contribute to matthewearl/q1physrl development by creating an account on GitHub.
2020 · github.com · its alternatives →
11
A Implementation of Alpha Zero for Chess in MLX▲71
A chess engine implementation inspired by AlphaZero, using MLX for neural network computations and Monte Carlo Tree Search (MCTS) for move selection.
2025 · github.com · its alternatives →
12
Building an LLM from Scratch in TypeScript▲33
The from-scratch guide to building large language models in NodeJS.
10d ago · book.humanexperiences.io · its alternatives →
13
Terminal-Bench-RL: Training long-horizon terminal agents with RL▲125
After training calculator agent via RL, I really wanted to go bigger! So I built RL infrastructure for training long-horizon terminal/coding agents that scales from 2x A100s to 32x H100s (~$1M worth of compute!) Without any training, my 32B agent hit #19 on Terminal-Bench leaderboard, beating Stanford's Terminus-Qwen3-235B-A22! With training... well, too expensive, but I bet the results would be good! *What I did*: - Created a Claude Code-inspired agent (system msg + tools) - Built Docker-isolated GRPO training where each rollout gets its own container - Developed a multi-agent…
2025 · github.com · its alternatives →
14
OpenAI Gym▲147
Open source interface to reinforcement learning tasks
2016 · its alternatives →
15
LeanRL: Fast PyTorch RL with Torch.compile and CUDA Graphs▲53
We're excited to announce that we've open-sourced LeanRL, a lightweight PyTorch reinforcement learning library that provides recipes for fast RL training using torch.compile and CUDA graphs. By leveraging these tools, we've achieved significant speed-ups compared to the original CleanRL implementations - up to 6x faster! Reinforcement learning is notoriously CPU-bound due to the high frequency of small CPU operations. PyTorch's powerful compiler can help alleviate these issues, but comes with its own costs. LeanRL addresses this challenge by providing simple recipes to accelerate your…
2024 · github.com · its alternatives →
16
Multi-GPU Reinforcement Learning in Tensorflow for OpenAI Gym▲58
Multi-GPU reinforcement learning using Deep Q-Network in TensorFlow for OpenAI Gym - vishar0/dist-dqn
2016 · github.com · its alternatives →
17TT
Text to 3D simulation on a map (does history pretty well)▲72
Simulate anything on a map from a text prompt -- and conduct risk analysis against LiveUA map's global realtime data points from social media and news sources. I trained a GPT-2-size model on historical incident data used to predict things that will go wrong. As historian Benjamin Breen mentions, the leading language models are good historians, so the application will simulate historical events pretty well also. I include a Multi-Agent RL Urban Mobility model in progress displayed on the map as small white cubes representing traffic and pedestrians. Around SF, it uses real census data and…
2025 · mused.com · its alternatives →
18
RLSL – Reinforcement Learning for Skip Lists (DBs and AI)▲9
Reinforcement Learning for Skip Lists. Contribute to cioc/rlsl development by creating an account on GitHub.
2018 · github.com · its alternatives →
19
Neural Network Evolution Playground with Backprop NEAT▲73
2016 · blog.otoro.net · its alternatives →
20
Genetic Algorithm Cars▲77
Breed cars and make them evolve with natural selection.
2015 · rednuht.org · its alternatives →
21
Iteratively Building Virtual Creatures in Minecraft▲49
"Creatures" is a stretch given that the environment is Minecraft, but the idea is simple: iteratively add blocks conditionally (tensor convolution) on the current environment (blocks) to maximize some reward. In this case I use PPO RL to train creatures to touch a glowstone block but you can adapt it to use any algorithm and reward (easily, as it uses the Ray framework). What I like about this work: iteratively finding solutions has a long and colorful history of doing things well: gradient boosting, ResNets, Stable Diffusion, etc. We're after some end optimal state and usually try to get…
2024 · github.com · its alternatives →
22
We Built an Autonomous RC Car Using Neural Networks and Raspberry Pi▲23
Autonomous RC car using Raspberry Pi and ANN. Contribute to multunus/autonomous-rc-car development by creating an account on GitHub.
2016 · github.com · its alternatives →
23RE
RULER – Easily apply RL to any agent▲81
Hey HN, Kyle here, one of the co-founders of OpenPipe. Reinforcement learning is one of the best techniques for making agents more reliable, and has been widely adopted by frontier labs. However, adoption in the outside community has been slow because it's so hard to implement. One of the biggest challenges when adapting RL to a new task is the need for a task-specific "reward function" (way of measuring success). This is often difficult to define, and requires either high-quality labeled data and/or significant domain expertise to generate. RULER is a drop-in reward function that works…
2025 · openpipe.ai · its alternatives →
24
Monostate AItraining▲59
Fine-tuning, RL, and inference in one CLI
Dec 2025 · github.com · its alternatives →

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