Grid-world

Grid-world is a benchmark dataset used to evaluate deep reinforcement learning algorithms by simulating an environment where agents navigate a grid to achieve specific goals.

Papers using Grid-world (2)

Federated Deep Reinforcement Learning2019 · 86 citesCAESAR: Enhancing Federated RL in Heterogeneous MDPs through Convergence-Aware Sampling with Screening2024 · 2 cites