Hi Marek,

We're talking about NuPIC as a data processor here, not the neocortex. If
some of your data is a function of the time, then time is a valid input.
Replacing actual data with empty records is a hack, not the other way
round. And non-data is not valid for the neocortex either. At night we just
sleep, and in fact we generate our own inputs just to keep the machine
running. Pardon me if I come across as brusque; it's very late here, and
I'm still recovering from jet lag...

Regards,

Fergal Byrne


On Fri, Nov 15, 2013 at 1:25 AM, Marek Otahal <[email protected]> wrote:

>
>
>
> On Fri, Nov 15, 2013 at 2:03 AM, Fergal Byrne <[email protected]
> > wrote:
>
>> Hi Mark,
>>
>> As I explained, time is often a datum in its own right. When learning the
>> cycles of power consumption in hotgym, the time of day and day of the week
>> are the most important determiners of power usage - the gym is closed at
>> night and there are peaks before and after the business day as people go to
>> the gym before and after work. Time in this sense is data just like any
>> other kind.
>>
>
> Yes, and I argue this can be achieved as well by a sequence
> ooXXXooooooXXXXX__________ , representing morning and evening queue, and
> empty at night. I'm not saying exp time is wrong, I mean it isn't
> biologically correct and (we should test if) it's possible to replace it
> with implicit time.
>
>
>>
>> In NuPIC, you don't do anything between inputs. The inputs decide the
>> timesteps - one per record, and NuPIC runs only when you call it with a new
>> record. NuPIC learns sequences, but there's no "between" between any two
>> timesteps.
>>
>
> What do you actually mean by timestep? To achieve learning, you need to
> boost connections between events at the (nearly) same times, and inhibit
> distant (meant on time scale) ones.  So if you touch redhot plate, and pain
> arrives 1hr later, nothing is learned from this unfortunate event.  If it
> hurts 1-2 secs after, you learn not to touch that again. To achive this, I
> imagine there's a penalty for every "time step" (unless boosted by
> co-occuring events). timestep is minimal time your sensors can distinguish
> (1/24th sec for eye, 1/100 sec for neuron), a refresh rate. At each step,
> connections that are both ON are boosted, other are inhibited.
>
> From the programming side, I said it's a hack, so I sure could decrease
> permanences before computing new input.
>
> Thanks, M.
>
>>
>> Regards,
>>
>> Fergal Byrne
>>
>> --
> Marek Otahal :o)
>
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>
>


-- 

Fergal Byrne, Brenter IT

<http://www.examsupport.ie>http://inbits.com - Better Living through
Thoughtful Technology

e:[email protected] t:+353 83 4214179
Formerly of Adnet [email protected] http://www.adnet.ie
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