The more I learn about fencing, the more it resembles stochastic processes and reinforcement learning, with each action being an optimization problem based on spatial position and opponent state. The fundamentals of point control map perfectly to error minimization and probability distributions, while bout strategy is essentially an exploration-exploitation problem with state-action value functions. Fencing ≈ Applied ML with Swords
![Shoe Story | Fencing Tutorial [Movement Style] (Foil, Epee, Saber)](/img/n.gif)
The more I learn about fencing, the more it resembles stochastic processes and reinforcement learning, with each action being an optimization problem based on spatial position and opponent state. The fundamentals of point control map perfectly to error minimization and probability distributions, while bout strategy is essentially an exploration-exploitation problem with state-action value functions.
Fencing ≈ Applied ML with Swords
Interesting perspective!
Honestly, this is an incredible summation. Throw in some game theory and you've nailed it
Love your videos, i always learn something new