Pinned Repositories
Auctions
Super simple auction environment.
dreamerv3-1
Mastering Diverse Domains through World Models
Easy21RL
Attempt at the UCL 2015 David Silver Reinforcement Learning Course Assignment
JAX-MAML
Super simple implementation of MAML for RL in JAX
popjym
POPGym Library in JAX
RL-Algorithms
Jupyter Notebooks of minimal Reinforcement Learning Algorithms
Stoix
🏛️A research-friendly codebase for fast experimentation of single-agent reinforcement learning in JAX • End-to-End JAX RL
IQA
Extensions to Yuan et al. QAit task.
flashbax
⚡ Flashbax: Accelerated Replay Buffers in JAX
RepGraph
MRP Frameworks graph visualisation and analysis tool
EdanToledo's Repositories
EdanToledo/Stoix
🏛️A research-friendly codebase for fast experimentation of single-agent reinforcement learning in JAX • End-to-End JAX RL
EdanToledo/JAX-MAML
Super simple implementation of MAML for RL in JAX
EdanToledo/Auctions
Super simple auction environment.
EdanToledo/popjym
POPGym Library in JAX
EdanToledo/RL-Algorithms
Jupyter Notebooks of minimal Reinforcement Learning Algorithms
EdanToledo/dreamerv3-1
Mastering Diverse Domains through World Models
EdanToledo/EdanToledo
EdanToledo/jax-dreamer
Dreamer on JAX
EdanToledo/Robotics-3D-Potential-Fields
EdanToledo/ai-economist
Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).
EdanToledo/Basic-NN
Basic Neural Network that uses either a threshold or sigmoid activation function. Nodes use the perceptron learning rule.
EdanToledo/clrs
EdanToledo/Connect-Four-Against-AlphaZero
Simple hack to existing connect 4 javascript app to allow for AlphaZero model to play online
EdanToledo/CSC3022F-Huffman-Encoding
C++ implementation of a huffman tree and encoding - Compress and Decompress text files
EdanToledo/CSC3022F-K-Means-Clustering
K means clustering assignment for CSC3022F
EdanToledo/L48-Taxation-Analysis
EdanToledo/Cardio
Cardio reduces boilerplate code by providing simple, lightweight environment interaction loops to make implementing deep reinforcement learning algorithms easy, intuitive, and readable.
EdanToledo/dejax
Accelerated replay buffers in JAX
EdanToledo/DQN-and-Actor-Critic-PyTorch
Really simple implementation of DQN in pytorch for gym environments
EdanToledo/DuelingDDQN-and-AlphaZero
Implementation of DQN, DDQN and Dueling (D)DQN to play Pong. AlphaZero implementation to play Connect4
EdanToledo/gym-hack
A toolkit for developing and comparing reinforcement learning algorithms.
EdanToledo/gymnax
RL Environments in JAX 🌍
EdanToledo/IQA
Extensions to Yuan et al. QAit task.
EdanToledo/marl-eval
A tool for aggregating and plotting MARL experiment data.
EdanToledo/Mava
🦁 A library of multi-agent reinforcement learning systems and components
EdanToledo/meltingpot
A suite of test scenarios for multi-agent reinforcement learning.
EdanToledo/PCA
Answering PCA Question Assignment 5
EdanToledo/R255-ImitationLearning
EdanToledo/REINFORCE-PyTorch
Simple Implementation of REINFORCE and PPO
EdanToledo/VectorizedMultiAgentSimulator
VMAS is a vectorized framework designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.