Lightweight multi-agent gridworld Gym environment

Simple grid-world environment compatible with OpenAI-gym

Gridworld environments for OpenAI gym.

Accelerated minigrid environments with JAX

Simple Grid Environment for Gymnasium

python package for fast shortest path computation on 2D polygon or grid maps

A simple Gridworld environment for Open AI gym

Value iteration, policy iteration, and Q-Learning in a grid-world MDP.

R.L. methods and techniques.

Tabular methods for reinforcement learning

A modular, extensible, entity-component-system (ECS) gridworld environment

Adversarial attacks in consensus-based multi-agent reinforcement learning

Approximate Dynamic Programming assignment solution for a maze environment at ADPRL at TU Munich

Safety challenges for AI agents' ability to learn and act in desired ways in relation to biologically and economically relevant aspects. The benchmarks are implemented in a gridworld-based environment. The environments are relatively simple, just as much complexity is added as is necessary to illustrate the relevant safety and performance aspects.

Old and new Reinforcement Learning algorithms run on the GridUniverse ecosystem

Simple implementation of text-based Gridworld game. Intended for use with reinforcement learning algorithms.

CSCI 561 - USC

Get started with Machine Learning in TensorFlow with a selection of good reads and implemented examples!

Create new gridworld gym environments easily

Implementations of model-based Inverse Reinforcement Learning (IRL) algorithms in python/Tensorflow. Deep MaxEnt, MaxEnt, LPIRL