Recent content by daniel_signal

A useful way to understand Reinforcement Learning is to separate the goal, the input, the model or tool, and the way the output is evaluated. One important area is setup choices. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can...

For Device Reviews, it helps to think in terms of inputs, constraints, verification, and iteration. One important area is performance. Define what a good result looks like before changing tools or settings, then test one variable at a time so you can tell what actually improved the outcome...