Building a Custom 8×8 GridWorld with Q‑Learning in Gymnasium

This tutorial walks through creating a custom 8×8 GridWorld environment in Gymnasium, implementing a Q‑Learning agent that learns to navigate from the top‑left corner to the bottom‑right goal while avoiding walls, and visualizing training curves, learned policies, and a performance comparison with a random agent.

GridWorldGymnasiumPython

0 likes · 10 min read

Building a Custom 8×8 GridWorld with Q‑Learning in Gymnasium

AI Algorithm Path

May 19, 2025 · Artificial Intelligence

Understanding Policy Evaluation and Improvement in Reinforcement Learning

This article explains how to solve Bellman equations, use iterative policy‑evaluation methods, apply the policy‑improvement theorem, and combine both steps in policy iteration, value iteration, and asynchronous variants, illustrated with a 5‑state example and a 4×4 gridworld.

Bellman equationGridWorldgeneralized policy iteration

0 likes · 15 min read

Understanding Policy Evaluation and Improvement in Reinforcement Learning