Studying Intelligence Thru Entropy?

An Anonymous Coward asks: "Given that entropy is the measure of order or disorder. Given that any force that changes the entropy of any system in a predictable way is an 'intelligent' force. Is it true that the study of HOW entropy changes in any given system is the study of intelligence itself, in that given system? I is it true that producing systems whose sole purpose it is to capture and synthesise changes in entropy is the production of intelligent systems?"

"A case in point. Neural networks are weighted switches. They store their 'weights' in the neuron. The storage of these weights determines the networks ability to perform an intellectual task. Therefore studying the 'entropy' of these weights and what and how they change and the effects of these changes is to study the networks 'intelligence' directly?

Another case in point. Genetic algorithms can search a solution landscape and then select the 'best' solution as a seed to the next iteration. This 'best current solution' will have an entropy or measure of order or disorder. So, in these terms, the system is measuring the level of chaos in the system according to some rules and selecting the solution that produces the least chaos (most entropy)

Is this striking any cords with anyone?"

Comments

Entropy and information

[algaeman]

Negative changes in entropy are information, not necessarily intelligence. Intelligence has connotations that information does not. Therefore, while several tons of algae are able to produce more information (by converting CO2, H2O and energy into carbohydrates) than a similar mass of humans, I suspect that the humans possess more intelligence. I think in order to have an intelligent discussion on the subject, an effective definition of intelligence would be needed. Not being a cognitive psychologist, I'll leave that to the experts and go on growing tons of algae.

Nah.

[Black Parrot]

> Given that any force that changes the entropy of any system in a predictable way is an 'intelligent' force.

The second law of thermodynamics is pretty predictable, but it has nothing to do with intelligence. Unless you consider randomly colliding molecules to be functionally intelligent.

No flame intended, but have you by any chance been listening to the proponents of "intelligent design theory", the latest reincarnation of creation 'science'?

> A case in point. Neural networks are weighted switches. They store their 'weights' in the neuron. The storage of these weights determines the networks ability to perform an intellectual task. Therefore studying the 'entropy' of these weights and what and how they change and the effects of these changes is to study the networks 'intelligence' directly?

You seem to be confusing the training of the network with its operations after it has been trained.

> Another case in point. Genetic algorithms can search a solution landscape and then select the 'best' solution as a seed to the next iteration. This 'best current solution' will have an entropy or measure of order or disorder. So, in these terms, the system is measuring the level of chaos in the system according to some rules and selecting the solution that produces the least chaos (most entropy)

Actually, depending what problem the GA is working working on and what exactly you measure for the entropy calculations, the entropy may either increase or decrease as it progresses. (I know this for a fact, because I've done it.)

> Is this striking any cords with anyone?

Yeah, the same kind Lister strikes when he plays his guitar on Red Dwarf.

There is certainly room for applications of entropy to the study of these things, but you don't seem to be off to a good start. For some basic applications of information theory to neural networks, see Haykin's textbook. There's surely lots more literature out there, if you care to track it down.