Marble Run 2D vs RL Playground

Welcome to the world of Marble Run 2D, where you can create and design your own marble tracks! In this captivating game, you become the architect of your own gravitational mazes, filled with amazing obstacles and thrilling challenges. - Create Your Own Tracks: You are the master builder, bringing your boldest ideas to life by constructing unique marble mazes. - Dive into Engaging Puzzles: Discover the thrill and satisfaction of overcoming various obstacles and solving complex puzzles. - Utilize Diverse Construction Elements: Your imagination knows no bounds! Take advantage of a wide range of elements to create the most intriguing tracks. - Earn Bonuses and Rewards: Successfully completing levels rewards you with unique bonuses and opportunities to enhance your track. - Immerse Yourself in Captivating Gameplay: Enjoy the process of creating and testing marble tracks in an engaging 2D atmosphere. Join the Marble Run 2D community today and immerse yourself in the captivating world of construction and puzzles that will keep you coming back for more! Terms of Use https://www.apple.com/legal/internet-services/itunes/dev/stdeula/ Privacy Policy https://patyukgames.blogspot.com/2017/02/normal-0-false-false-false-ru-x-none-x.html

RL Playground is a one-of-a-kind interactive experience to explore reinforcement learning through play Agents don’t fake learning here — they actually learn, locally, on your device. No cloud, no servers, no precomputed simulations. You can watch learning happen live, episode after episode. Each level is based on a concrete scenario: a drone learning when to jump over a gap, an autonomous car learning to avoid pedestrians, a Duck Hunt–inspired challenge focused on tracking and decision-making. You can tweak learning parameters, train the agent, then test it and observe how its behavior evolves over time. RL Playground is made for: people who want to understand AI hands-on, curious minds, students, developers, and players looking for experimental, meaningful games. No internet required. No prior ML knowledge needed. Just learning by doing.