Solomonoff Induction is empiricist because it assumes all knowledge comes from the data. Theories arising from Solomonoff Induction are, at most, only as reliable as the data and it can’t come up with theories that make more precise predictions than the data or that contain more knowledge than the data. This is complicated by the fact that in real life applications it will have to deal with noise in the data and this is going to get deeply subjective very quickly.
Another problem is: how is the dataset itself constructed? You don’t just go out and collect data; you need to know what you are looking for. Among the infinite number of things you can observe, you need to know what is important and to know this you need a theory. Where does this theory come from? It arises as a conjectural explanation to a problem-situation and specific predictions arising from the explanation guide your observations. So Solomonoff Induction has things backward.
Solomonoff Induction is just about prediction. It models a forecasting agent that observes a stream, and emits probabilities of the next symbol. It doesn’t do anything else. Complaining that it can’t create its own experiments seems rather futile. Of course it can’t—it is a forecaster. Real agents do more than just forecast, of course, but that isn’t a criticism for forecasting, or the idea of a forecaster.
Solomonoff Induction is empiricist because it assumes all knowledge comes from the data. Theories arising from Solomonoff Induction are, at most, only as reliable as the data and it can’t come up with theories that make more precise predictions than the data or that contain more knowledge than the data. This is complicated by the fact that in real life applications it will have to deal with noise in the data and this is going to get deeply subjective very quickly.
Another problem is: how is the dataset itself constructed? You don’t just go out and collect data; you need to know what you are looking for. Among the infinite number of things you can observe, you need to know what is important and to know this you need a theory. Where does this theory come from? It arises as a conjectural explanation to a problem-situation and specific predictions arising from the explanation guide your observations. So Solomonoff Induction has things backward.
Solomonoff Induction is just about prediction. It models a forecasting agent that observes a stream, and emits probabilities of the next symbol. It doesn’t do anything else. Complaining that it can’t create its own experiments seems rather futile. Of course it can’t—it is a forecaster. Real agents do more than just forecast, of course, but that isn’t a criticism for forecasting, or the idea of a forecaster.