Applications of Machine Learning
It turns out that optimizing warehouse tasks is hard.
It turns out that optimizing warehouse tasks is hard.
I’ve been reading a lot of Searle recently. Searle bashing seems to be a popular pastime among young graduate students in AI, but I admit to a certain sympathy with his argument. I recently read about analogue computing in The New Turing Omnibus which reminded me of one of Searle’s central claims, that the locus [...]
As I near completion on my final project for a course on reinforcement learning, I came across the following from Sutton’s page on tile coding: With the code described so far, there is a small probability that unrelated inputs will hash into some of the same tiles. In a group of tilings, usually there will [...]
The most interesting problems, the task of feature discovery for example, are not ones that Gaussian processes will solve. But maybe multilayer perceptrons can’t solve them either. Perhaps a fresh start is needed, approaching the problem of machine learning from a paradigm different from the supervised feedforward mapping.