I guess author makes the distinction from deterministic Vs non-deterministic algorithms. As a layman in these matters I still don't fully understand how some people classify machine learning algorithms as non-deterministic...
...i started wondering about this when I was reading a few articles about the AlphaZero algorithm that learned to play chess entirely from self play and wondered if it would always play the same moves in response to a fixed set of opponent moves (assuming the opponent starts as white).
My guess was that it wouldn't always respond in exactly the same way in case there's any MCTS like step somewhere in there blended with the Machine learning algorithm.
For a game like chess it would seem to make sense that the overall algorithm would still include a MCTS step (like AlphaGo did) but for an autonomous car it would seem crazy to any human to imagine that there would be any random search for a decision in a tree of possible interpretations of the input for example.
Does any one have any detailed knowledge about this? Would a non-deterministic algorithm ever be allowed in an autonomous car?
> As a layman in these matters I still don't fully understand how some people classify machine learning algorithms as non-deterministic...
Some algorithms start with random numbers for the model and converge towards a better model. After the model is generated the input->output will be deterministic, but since the model generation is non-deterministic the algorithm overall is considered non-deterministic.
