[From Rick Marken (951229.0830)]

Shannon Williams (951228)---

In _The Philosophy of Artificial Intelligence_, Andy Clark briefly

describes PDP (Parallel Distributed Processing).

I see a couple of ways to change the system:

1) Since a reference level exists, the unit should continuously 'adjust the

weights on the hidden units' until the correct output is generated...

5) I can see atleast one way that the reference generator can evolve: Let

the first letters be input...

What do you think of this project?

It's hard for me to tell from your verbal description. Could you provide a

simple diagram of what you would like to do?

Here's what I think you might mean:

r

>

v

---> C --- e

p |

> adjust

> k weights

> s | |

^ |

> >

> v

[i-->|o = sum(ki)| -->o]

This control system adjusts the weights (k values) of a linear pattern

recognizer (o = sum(ki)). The weights of the pattern recognizer are to be

adjusted so that inputs (i, sound patterns) are converted into appropriate

outputs (o, phonemes ). The control system must perceive the relationship

between i and o; so the control system's perceptual function, s, is a

relationship recognizing function.

Let's say that s is designed so that when the relationship between any i and

any o produces a perceptual value of zero (0) the relationship is what a

linguist considers the "correct" mapping of sound input to phonemic output;

non-zero perceptual values measure the discrepency of the relationship from

this "correct" mapping. This way the reference input to the control system

can be fixed at 0. The output of the perceptual function, p, is quantitative

so that there is always a quantitative error signal, e = r-p. Non-zero error

values are turned into adjustments to the k weights of the pattern

recognizer.

This system would continuously adjust the k weights of the pattern recognizer

until the output of the control system's perceptual function, s, (the measure

of relationship between i and o) is at the reference value (0), if such a

solution exists.

Of course, the tough part of designing this automatic "learning" control

system is designing 1) the function, s, that perceives the relationship

between i and o and 2) the error-driven weight adjustment algorithm -- though

this could probably be an E. coli style random process.

Is this close to what you had in mind?

Best

Rick