○ unseen · kind algorithm · level 0 · 3h
- Implementa: Reinforcement Learning
Optimises the policy directly by ascending the gradient of expected reward. The family (REINFORCE, PPO) behind continuous control and RLHF.
Stochastic Gradient Descent is an iterative method for optimizing an objective function with suitable smoothness properties. It can be regarded as a stochastic approximation of Gradient Descent optimization, since it replaces the actual gradient by an estimate thereof. Especially in high-dimensional optimization problems this reduces the very high computational burden, achieving faster iterations in exchange for a lower convergence rate.
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- Implementa: Reinforcement Learning