Artificial Intelligence
We haven’t had a thread, well not for some time anyway, that was devoted completely to the subject of AI, yet it still rears it’s head from time to time in the context of other arguments.
So I thought I’d start one.
Firstly, what is it that we define as intelligence? Whilst avoiding the well known, and much abused Turin Test, my – rather poor – starting definition is that intelligence is
http://en.wikipedia.org/wiki/Intelligence_(trait)
One presumes that this list is what needs to be satisfied in order to produce discrete components that can be certified as artificially intelligent.
It seems like a nasty incongruent, and effectively impossible, list, but I think that most of it might be achievable.
I’ll try to deal with the first:
(i) The Ability To Reason
The ability to reason is implied in many applications’s today. From games theorist’s game-trees, and game-matrices to compiler technology, Bayesian implication, and backward chaining.
One, though, jumps (not literally) out at me. Backward chaining traverses graphs of a given set of choices from a given conclusion. This holds as the justification of a decision made, and these techniques are used to get expert systems to statistical justify what it is that lead them to make a deduction from the supplied assertion.
I would like to assert that the antonym of a ‘justification made’, is, in fact the ‘process of reasoning’. Each one traverses different directions on a planar graph. Using Bayesian implication (weight the vertices), and perhaps some form of light neural network technology (weight the edges) an agent, I believe, could make rational decisions on the information at hand.
(Those more verse in these techniques will recognise that this is in fact the architecture of a neural network but instead of summation firing function in the neuron we will be using Bayesian techniques)
The neural techniques would provide the plumbing; possibly for efficiency, randomisation, and perhaps some implied reasoning. In particular implied reasoning would, given a particular input assertion, automatically imply a given deduction. This may, perhaps (very perhaps), mimic instinct. Clearly this would have to pre-built for each species built and that could be easily achieved using evolutionary techniques. One of the goals being basic stuff like ‘if there’s food and I’m hungry, then eat the food’
The Bayesian techniques would always be subject to some form ongoing training program; perhaps the absolute square of differences (it’s fast efficient and not particular prone getting stuck on local minima although if the decision is non-linear it can sometimes get stuck) In the case of the ‘if there’s food and I’m hungry, then eat the food’ the Bayesian weighting, by experience, could recognise poisonous food, and override the neural weightings.
I believe that the marriage of the three technologies. Evolutionary programming, neural networks, and Bayesian implication are the simple rules that could set the foundation for the emergence of what we, as humans, might determine as intelligent.
What do you guys think?
Anyone any ideas on the other items on the list?