Open AI Hide & Seek Revolutionizes Reinforcement Learning

Timestamps
[00:00:00] – Evoke Childhood Hide-and-Seek Hook
[00:00:12] – Reveal OpenAI’s Game Setup
[00:00:39] – Define Blue Hiders vs Red Seekers
[00:01:37] – Explain Reinforcement Learning Loop
[00:02:23] – Show Ramp Defense Tactic
[00:03:26] – Demonstrate Box Surfing Trick
[00:05:50] – Examine Agent Policy Architecture
[00:08:30] – Explore Advanced Emergent Strategies
[00:10:31] – Wrap-Up & Like/Subscribe Prompt

Hopefully y'all enjoyed the video, I have been wanting to talk about this for a long time!!
Here is a small explanation from Open AI's Website:

We’ve observed agents discovering progressively more complex tool use while playing a simple game of hide-and-seek. Through training in our new simulated hide-and-seek environment, agents build a series of six distinct strategies and counterstrategies, some of which we did not know our environment supported. The self-supervised emergent complexity in this simple environment further suggests that multi-agent co-adaptation may one day produce extremely complex and intelligent behavior.

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