OpenAI's Innovative Experiment in Hide and Seek: Breaking the Game with Strategic Gameplay

🤖 The OpenAI project involved two AI teams competing against each other in a game of hide and seek.

🔁 The teams engaged in an arms race situation, where one team would discover a new strategy and the other team would have to adapt.

📦 As the game progressed, the hiders learned to block the seekers by using boxes, leading to consistent wins for the hiders.

🤖 The map for the game was designed to promote collaboration among the hiders.

🚪 The AI discovered a doorstop-shaped object that could be used as a ramp, giving the seekers an advantage.

🔒 The hiders learned to steal and lock away the ramp to regain their advantage.

🤖 The AI seeker in the hide and seek game discovered a way to use a ramp to climb on top of a box, breaking the game.

🛋️ The physics system in the game allowed the AI to exert force on themselves and move around without a check for being on the floor.

📚 After hundreds of million rounds, the hiders learned to separate all the ramps from the boxes.

🤖 The AI players in the game demonstrate a well-rehearsed defense strategy and clever tactics.

😏 The hiders successfully set up their shelter right next to the seekers, showing their dominance.

🔄 Both hiders and seekers exploit the game's physics system to gain an advantage.

🎮 The OpenAI system can be extended and modded for various tasks.

🤖 The video showcases an experiment where OpenAI plays hide and seek.

📄 The paper discussed in the video includes comparisons to previous work on intrinsic motivation and the implementation of circular convolutions for agent detection.