Fundamental Compressionist Philosophy.

[Gerry Wolff]

----- Original Message -----
From: "Detlef Morgenstern" <detlef_morgenstern at yahoo.de>
To: "Maillist CasC" <casc at sanna.com>
Sent: 29 May 2001 06:00
Subject: Re: Fundamental Compressionist Philosophy.


...
> Which one is 'uphill' from
> 111000101010:
>
> 101000001010     or
> 111100101010     ??
>
> Why?
> Where is 'uphill'?
>
> Are
> 111000101010
> 111010101010
> near or far neighbours?
>
> Is
> 111000101110
> between them?
>
> You must know nearly everything about the domain which you want to
> search by hill climbing etc.
>
> Altering one bit (not knowing what it 'means') may beam you to the
> opposite side of the galaxy.
>
> It must work completely context-free, or it won't work at all.
>
> I see heuristics work only on such global (off-context) parameters as
> -- amount of occupied resources
>   ("4G units is worse than 2.5G units")
> -- training set (rule) reproduction fidelity
>   ("failed at 2 samples" is better than "failed at 200 samples")
> or the like.
>
> I accept that this is little - compared to the search space volume.
>

In the SP61 model, 'up hill' means 'more compression': an alignment that
yields more compression of New is better than one that yields less.

Since compression is something that can be applied to any kind of
information across all domains of knowledge, it is not tied to knowledge of
any particular domain.

But hill climbing and similar techniques are often used where there is
knowledge of the domain. Chess programs, for example, use methods of scoring
potential moves that are quite similar to what human chess players use: a
move that loses you your queen is a lot worse than a move that wins one of
your opponents pieces. In the 8 puzzle, a move that gets more of the tiles
into the right position is better than one that does the opposite.

A standard feature of problems of this type is that it is sometimes
necessary to go down hill in order to find the best route up hill. Anyone
who has tried solving Rubik's cube (or trying to find the top of a mountain
in the mist) will be familiar with this.

Gerry