Lecture 15
The Frame Peroblem
All we have are axioms. Some set of limited finite set of them to determine change.
All the axioms grow expodentiallly, so that sort of thing doesn't work. It might work in a small toy world, but not in the real world.
R&N try things, but it requires the robot to know exhaustively what can and cannot happen in the world, and encode it into the rebot.
There is this such approach in AI.
Another approach is allowing these things to be constructed on the fly, with the robot learning about the world as it exists in it.
Up until now there's been traditional search,
The Many Frame Problems
Lecture 15
Nonmonotonicity and Defeasable Reasoning.
The Japanese 5th generation project.
Japanese producing AI machines that would dominate the world. The 80s scare.
The enormous cauldron you throw all these axiomised things into and then things warm up, suddenly boom you have an AI
Minsky "A framework for representing knowledge".
Logic can't be the right vehicle for knowledge representation.
People are inconsistent! It would be easy to create an AI that can always say "Yes".
Therefore AI needs means of dealing with inconsistency.
The AI has to be able to generalise, which means it has to be able to accept mistakes.
I think I'm interested and most believing in neural networks for AI, considering that I think it's like solving the meta problem, and it also simulates the brain.
The goal of building a neural network would be to create the architecture for it to begin learning, and to train it in language, any language, and then use that naturally learnt language to associate real world objects to those objects within the same net.
It would just be a monitor-able, extremely diligent and quick student.
It could learn all human languages, and therefore learn everything that humans know.
If we made a deaf man hear for the first time, would he understand the language he can read and write in?
Because this has implications for an AI who could read and write, but had not been given ears.
You cannot convey the same amount of emotion and emphasis through writing as you can with voice.
All we have are axioms. Some set of limited finite set of them to determine change.
All the axioms grow expodentiallly, so that sort of thing doesn't work. It might work in a small toy world, but not in the real world.
R&N try things, but it requires the robot to know exhaustively what can and cannot happen in the world, and encode it into the rebot.
There is this such approach in AI.
Another approach is allowing these things to be constructed on the fly, with the robot learning about the world as it exists in it.
Up until now there's been traditional search,
The Many Frame Problems
Lecture 15
Nonmonotonicity and Defeasable Reasoning.
The Japanese 5th generation project.
Japanese producing AI machines that would dominate the world. The 80s scare.
The enormous cauldron you throw all these axiomised things into and then things warm up, suddenly boom you have an AI
Minsky "A framework for representing knowledge".
Logic can't be the right vehicle for knowledge representation.
People are inconsistent! It would be easy to create an AI that can always say "Yes".
Therefore AI needs means of dealing with inconsistency.
The AI has to be able to generalise, which means it has to be able to accept mistakes.
I think I'm interested and most believing in neural networks for AI, considering that I think it's like solving the meta problem, and it also simulates the brain.
The goal of building a neural network would be to create the architecture for it to begin learning, and to train it in language, any language, and then use that naturally learnt language to associate real world objects to those objects within the same net.
It would just be a monitor-able, extremely diligent and quick student.
It could learn all human languages, and therefore learn everything that humans know.
If we made a deaf man hear for the first time, would he understand the language he can read and write in?
Because this has implications for an AI who could read and write, but had not been given ears.
You cannot convey the same amount of emotion and emphasis through writing as you can with voice.
posted by Mathieu at 3:47 PM
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