Kale-ab Tessera's repositories
Research-Paper-Reading-Template
A markdown template for taking notes to summarize research papers.
SuperSuit
A collection of wrappers for Gymnasium and PettingZoo environments (being merged into gymnasium.wrappers and pettingzoo.wrappers
BenchMARL
A collection of MARL benchmarks based on TorchRL
cleanrl
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
Shimmy
An API conversion tool for popular external reinforcement learning environments
PRM-Path-Planning
Implementation of Probabilistic Roadmap Path Planning Algorithm.
personal-site-v2
My personal website.
Policy-Gradient
Implementation of the following Policy Gradient Algorithms -Reinforce and Actor Critic.
Mountain_Climbing_SARSA_Semi_Gradient
Implementation of SARSA Semi-Gradient Method on the Mountain Car Open AI Environment.
SARSA_Cliffwalking
Implementation of SARSA for cliffwalking environment.
Gridworld-Markov-Decision-Process
Implementing a gridworld from scratch and configuring it as a Markov decision process.
Multi-Armed-Bandit
Implementation of greedy, E-greedy and Upper Confidence Bound (UCB) algorithm on the Multi-Armed-Bandit problem.
on-policy
This is the official implementation of Multi-Agent PPO (MAPPO).
awesome-marl
A categorised list of Multi-Agent Reinforcemnt Learning (MARL) papers
off-policy
PyTorch implementations of popular off-policy multi-agent reinforcement learning algorithms, including QMix, VDN, MADDPG, and MATD3.
acme
A library of reinforcement learning components and agents
smac
SMAC: The StarCraft Multi-Agent Challenge
rigl
End-to-end training of sparse deep neural networks with little-to-no performance loss.
openpilot
openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for over 100 supported car makes and models.
loss-landscape
Code for visualizing the loss landscape of neural nets
scipy
Scipy library main repository
d2l-en
Dive into Deep Learning: an interactive deep learning book with code, math, and discussions, based on the NumPy interface.
boostnote-markdown-cheatsheet
📋 📘 The missing one page markdown feature cheat sheet for Boostnote
botorch
Bayesian optimization in PyTorch
Monte-Carlo-and-Temporal-Difference
Monte Carlo and Temporal Difference implementation from Chapter 5 and Chapter 6 of Reinforcement Learning: An Introduction Book by Andrew Barto and Richard S. Sutton.