Return to Answer

This would lead to the absurd conclusion that all algorithms would have to have a better than random chance of learning. Of course, that can't be the case, so any effective strategies must incorporate some prior knowledge about the nature of the problem. In other words, there's no such thing as a generic solution that can be expected to have anything better than purely random success. Any child born with such a system couldn't be expected to learn anything at all. Therefore, either the No Free Lunch Theorem is false or empiricism is false.

This would lead to the absurd conclusion that all algorithms would have to have a better than random chance of learning. Of course, that can't be the case, so any effective strategies must incorporate some prior knowledge about the nature of the problem. In other words, there's no such thing as a generic solution that can be expected to have anything better than purely random success in any task. Any child born with such a system might have a random chance of doing something right, but it could hardly be recognized as learning. Therefore, either the No Free Lunch Theorem is false or empiricism is false.

This would lead to the absurd conclusion that all algorithms would have to have a better than random chance of learning. Of course, that can't be the case, so any effective strategies must incorporate some prior knowledge about the nature of the problem. In other words, there's no such thing as a generic solution that can be expected to have anything better than purely random success. Any child born with such a learning system couldn't be expected to have any more than a 50% chance of learning anything. Therefore, either the No Free Lunch Theorem is false or empiricism is false.

This would lead to the absurd conclusion that all algorithms would have to have a better than random chance of learning. Of course, that can't be the case, so any effective strategies must incorporate some prior knowledge about the nature of the problem. In other words, there's no such thing as a generic solution that can be expected to have anything better than purely random success. Any child born with such a system couldn't be expected to learn anything at all. Therefore, either the No Free Lunch Theorem is false or empiricism is false.

This would lead to the absurd conclusion that all algorithms would have to have a better than random chance of learning. Of course that can't be the case, so any effective strategies must incorporate some prior knowledge about the nature of the problem. In other words, there's no such thing as a generic solution that can be expected to have anything better than purely random success. Therefore, either the No Free Lunch Theorem is false or empiricism is false.

This would lead to the absurd conclusion that all algorithms would have to have a better than random chance of learning. Of course, that can't be the case, so any effective strategies must incorporate some prior knowledge about the nature of the problem. In other words, there's no such thing as a generic solution that can be expected to have anything better than purely random success. Any child born with such a learning system couldn't be expected to have any more than a 50% chance of learning anything. Therefore, either the No Free Lunch Theorem is false or empiricism is false.