The Equation That Solves Itself

At the heart of reinforcement learning is a strange loop: an agent wants to know how good every square in a grid is, but the value of one square depends on the value of the next, which depends on the one after that — the thing it needs is defined by the very thing it's looking for. The Bellman equation resolves the loop in one line: the value of a state is the reward you collect now, plus gamma (a discount between zero and one) times the value of wherever you land next. Notice the value function sits on both sides of its own definition — that's not a bug, it's a constraint the true values have to satisfy. And a constraint like that can be solved by pure repetition: start with zeros everywhere, keep applying the equation, and value bleeds outward from the goal one ring at a time until the whole grid settles. The equation that defines itself is exactly the one that solves itself. #shorts *Follow Me* ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 🐦 X: @datamlistic https://x.com/datamlistic 📸 Instagram: @datamlistic https://www.instagram.com/datamlistic 📱 TikTok: @datamlistic https://www.tiktok.com/@datamlistic 👔 Linkedin: https://www.linkedin.com/company/datamlistic *Channel Support* ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ The best way to support the channel is to share the content. ;) If you'd like to also support the channel financially, donating the price of a coffee is always warmly welcomed! (completely optional and voluntary) ► Patreon: https://www.patreon.com/datamlistic ► Bitcoin (BTC): 3C6Pkzyb5CjAUYrJxmpCaaNPVRgRVxxyTq ► Ethereum (ETH): 0x9Ac4eB94386C3e02b96599C05B7a8C71773c9281 ► Cardano (ADA): addr1v95rfxlslfzkvd8sr3exkh7st4qmgj4ywf5zcaxgqgdyunsj5juw5 ► Tether (USDT): 0xeC261d9b2EE4B6997a6a424067af165BAA4afE1a #shorts #reinforcementlearning #machinelearning