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Next Unicorns: Empowering robots to think for themselves via AI with Covariant’s Peter Chen | E1796
This Week in Startups
Two fundamental concepts of reinforcement learning
Reinforcement learning involves learning from different actions and using a reward function to rate their outcomes. The agent explores the world by taking various actions, which are then rated by the reward function. The algorithm identifies the actions that tend to be better and continues the learning loop. There are technicalities in making it work efficiently and with other systems like GPT. In chess, the behavior choice is moving the pieces according to the rules, with the goal of not having pieces taken and ultimately winning the game.
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