Lightweight multi-agent gridworld Gym environment
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Updated
Sep 21, 2023 - Python
Lightweight multi-agent gridworld Gym environment
Accelerated minigrid environments with JAX
Gridworld environments for OpenAI gym.
Simple grid-world environment compatible with OpenAI-gym
Get started with Machine Learning in TensorFlow with a selection of good reads and implemented examples!
Simple Gridworld Gymnasium Environment
python package for fast shortest path computation on 2D polygon or grid maps
Tabular methods for reinforcement learning
Training (hopefully) safe agents in gridworlds
Value iteration, policy iteration, and Q-Learning in a grid-world MDP.
A simple Gridworld environment for Open AI gym
Old and new Reinforcement Learning algorithms run on the GridUniverse ecosystem
Adversarial attacks in consensus-based multi-agent reinforcement learning
Simple implementation of text-based Gridworld game. Intended for use with reinforcement learning algorithms.
Train agents on MiniGrid from human demonstrations using Inverse Reinforcement Learning
Small library for visualizing gridworlds by generating svgs styled and animated by css.
Implementation of Reinforcement Algorithms from scratch
The PyTorch framework developed to enable my MSci thesis project titled: "Evaluating Uncertainty Estimation Methods For Deep Neural Network’s In Inverse Reinforcement Learning"
Extended, multi-agent and multi-objective (MaMoRL / MoMaRL) environments based on DeepMind's AI Safety Gridworlds. This is a suite of reinforcement learning environments illustrating various safety properties of intelligent agents. It is made compatible with OpenAI's Gym/Gymnasium and Farama Foundation PettingZoo.
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