Hi Tom,

It sounds like your understanding is correct. The only part of your email I 
didn't understand was this:

> On the other hand, if I'm walking down the middle of the street you're going 
> to be uncomfortably close, but the geospatial encoder won't register this.

Can you elaborate on that?

- Chetan 

On January 11, 2015 at 9:24:00 PM, thomas taylor ([email protected]) 
wrote:

After a few days delay, I'm bringing this to the nupic list from the nupic 
theory list,  as suggested by Matt Taylor.
*********************************************
Message: 1
Date: Tue, 6 Jan 2015 12:53:07 -0700
From: thomas taylor <[email protected]>
To: [email protected]
Subject: a geocoder feature?
Message-ID:
        <CAGnmPQr0p85tzoHivoSfR=b178dsckt1jc2al-nwkkrpyi7...@mail.gmail.com>
Content-Type: text/plain; charset="utf-8"

Hi all, If this belongs on another list please point me in the right
direction.  I've been asked by the Cameron Hunt at the Center For Open
Exploration to think about their NuPIC use-case of anomaly detection for
their aircraft and ship data. After viewing Chetan's video
<http://www.youtube.com/watch?v=KxxHo-FtKRo> on the geocoder and track
anomaly detection, I'd like to check my understanding.

Take a situation in which you are encoding low speed object and a high
speed object, e.g. you driving on the freeway and me walking next to it.
When geocoder choses active squares in the box of the low speed object it
has relatively few squares to choose from. When the geocoder chooses the
same number of active squares for the high speed object, it has a much
larger number of squares to choose from. The highest ranking squares in the
larger box are likely to have higher rank than the squares in the smaller
box.  I *think*  what's going to happen is that there will be less overlap
between the active squares in nearby locations with different size boxes
than there is overlap in nearby locations with the same size boxes.  This
means, that the sparse bit string representations of the fast object and
the slow object will have little overlap.   In a sense this reflects one
kind of cognitive reality, when I'm walking along the sidewalk people
driving nearby might as well be in another Universe.  On the other hand, if
I'm walking down the middle of the street you're going to be uncomfortably
close, but the geospatial encoder won't register this.

Do I understand the situation?

thanks,
Tom Taylor
Volatus Logic, LLC
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Message: 2
Date: Tue, 6 Jan 2015 12:00:38 -0800
From: Matthew Taylor <[email protected]>
To: NuPIC theory mailing list <[email protected]>
Subject: Re: a geocoder feature?
Message-ID:
        <cajv6ndm_jfnoqjtoxq4pve7h2aksv_p--hqes388ttavc5s...@mail.gmail.com>
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Hi Tom, thanks for sending. Yes, I think your question probably
belongs in the nupic-discuss list.

See http://numenta.org/lists for descriptions of our mailing lists,
and please resend your question to [email protected] after
subscribing at 
http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org.

Thanks!
---------
Matt Taylor
OS Community Flag-Bearer
Numenta
------------------------------

Message: 3
Date: Wed, 7 Jan 2015 08:43:32 +0000
From: Fergal Byrne <[email protected]>
To: NuPIC theory mailing list <[email protected]>
Subject: Re: a geocoder feature?
Message-ID:
        <cad2q5yd6anjxgy5hw018pbaoj_bbbumoch27dovquddb9yw...@mail.gmail.com>
Content-Type: text/plain; charset="utf-8"

Hi Thomas,

That's a really good question.

The overlap of the two representations is proportional (on average) to the
ratio of the shared area to the high-speed area, so the overlap will
gracefully go down from 100% (at matching speeds). Since there is always a
minimum area, even at zero speed, there will always be a significant
commonality between two representations at the same location, and always a
significant difference for different locations. The idea neatly encodes the
subjective experience of how our "sense of place" degrades when we're
travelling very fast.

You're correct in surmising that this encoding is not suitable, per se, for
things like collision detection, but it might be adapted for things like
collision prediction, or at least for a useful "paranoid" safety system.
Because the encoding is very sparse, the overlap tells you how likely it is
that you (walking) are dangerously near me (driving). If there are any bits
in common between your SDR and my predicted next position, I should
probably use some other information to see if there's any danger.

A real navigation system using this encoder would likely use both the
standard spatial reference frame (ie Lat-Long on the Earth's surface) and a
vehicle-centred reference frame to model other road users. In this
scenario, if your trajectory relative to me was predicted to enter a small
area around me, I would sound an alarm if I detected any bits in common
with position (0, 0, speed).

Regards,

Fergal Byrne

--

Fergal Byrne, Brenter IT

http://inbits.com - Better Living through Thoughtful Technology
http://ie.linkedin.com/in/fergbyrne/ - https://github.com/fergalbyrne

Founder of Clortex: HTM in Clojure -
https://github.com/nupic-community/clortex

Author, Real Machine Intelligence with Clortex and NuPIC
Read for free or buy the book at https://leanpub.com/realsmartmachines

Speaking on Clortex and HTM/CLA at euroClojure Krakow, June 2014:
http://euroclojure.com/2014/
and at LambdaJam Chicago, July 2014: http://www.lambdajam.com

e:[email protected] t:+353 83 4214179
Join the quest for Machine Intelligence at http://numenta.org
Formerly of Adnet [email protected] http://www.adnet.ie
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