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'validate your reason for existence' relates directly to pattern learning.
The validation is a pattern of what is good about us, most simplistically
a reference to a past event we were involved in, where we contributed/succeeded.
Preferably a pattern of us being able to reproduce good events.
This is a way to learn to dance.
Say we have a habit that has an unknown delay before firing, and we want to fire
it in synchrony with an event. Our goal is to produce our event within a smaller
time window to the target event than in the past ("same time as").
Good: time window is closer than ever before.
need: history log to refer to good event.
please wait a little? expanding reference to good event into how-to-learn
need: behavior based on what-succeeded, what-failed
value metric?
SO! we want to learn how to time an event. We have some tools, for example:
- waiting for or until a given time
- getting the current time
- comparing two times
We want to combine the tools in a way that makes the event happen at the time
we want.
- doing something after the right time happens
- doing our event
Since each habit has an unknown delay, we might play with delaying a certain
time since the last event, until we find the right delay that works best for us
most of the time.
Testing metric: runs when event is fired, measures time between
event and right time. if time is less than ever before, success.
if time is significantly more than behavior's norm, failure.
Convert to English: try to have the event happen at the right time.
note metric will give random successes false status
A successful approach would be to adjust the delay towards the difference by
a small ratio.
The most successful approach would be to use the time difference to adjust the
delay precisely.
Ideally we would find solution #2 after trying solution #1.
The idea of 'moving towards' would adjust into 'moving the exact right
amount'.
In operators, this could be a development of the subtraction operator.
But using a value exactly is actually simpler than using a ratio of it.
So we can move from numbers towards ideas.
More. Less. More a lot? Less a lot? More a little? Less a little?
Ideally we use learning strategies that facilitiate learning
how to learn in general.
That means summarizing and acting on the meaning of pattern structures.
In reality, everything jitters a little bit. Nothing is ever exactly the same.
Things also grow and shrink over time.
Habits look to be needed, to have value.
As one ourselves, we look to relate to those that meet our needs, have value to
us.
The core habit, to learn, is the one that selects other habits and works with
them. Ideally it's an intermixing of existing habits.
What might a winning habit's structure look like? say it is the perfect one.
set to do 1ce on goal time:
ctx X
record time A
set to do 1ce on goal time:
record time B
trigger D1 for X
delay for C (X)
record time E
trigger D2 for X
When both D1 and D2 have been triggered for X:
calculate B - E, store in F
calculate F + C, provide as C for next context
will want to know which C is being used when we delay.
could be wrong C.
and we'll want to form structure promises ...
.. and map to meaning for operator
operator watches and understands as learning
develops, and provides labels for shared
understanding that develops.
operator will want generalization to happen
fast, so as to label shared meaning.
could also provide label-goals, and code must guess
towards goals, to get onto same page as operator.
I think in structuring such a large habit out of parts, we would find a lot
of learning relevence.
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