I spent a while back in the 90s trying to make AGI and alife converge,
before establishing to my satisfaction the approach is a dead end: we
will never have anywhere near enough computing power to make alife
evolve significant intelligence (the only known success took 4 billion
years on a planetary sized nanocomputer network, after all), even if
we could set up just the right selection pressures, which we can't.

On Tue, Jul 27, 2010 at 4:23 AM, Linas Vepstas <[email protected]> wrote:
> I saw the following post from Antonio Alberti, on the linked-in
> discussion group:
>
>>ALife and AGI
>>
>>Dear group participants.
>>
>>The relation among AGI and ALife greatly interests me. However, too few 
>>recent works try to relate them. For exemple, many papers presented in AGI-09 
>>(http://agi-conf.org/2009/) are about program learning algorithms (combining 
>>evolutionary learning and analytical learning). In AGI 2010, virtual pets 
>>have been presented by Ben Goertzel and are also another topic of this forum. 
>>There are other approaches in AGI that uses some digital evolutionary 
>>approach for AGI. For me it is a clear clue that both are related in some 
>>instance.
>>
>>
>>By ALife I mean the life-as-it-could-be approach (not simulate, but to use 
>>digital environment to evolve digital organisms using digital evolution 
>>(faster than Natural one - see 
>>http://www.hplusmagazine.com/articles/science/stephen-hawking-%E2%80%9Chumans-have-entered-new-stage-evolution%E2%80%9D).
>>
>>So, I would like to propose some discussion topics regarding ALIfe and AGI:
>>
>>1) What is the role of Digital Evolution (and ALife) in the AGI context?
>>
>>2) Is it possible that some aspects of AGI could self-emerge from the digital 
>>evolution of intelligent autonomous agents?
>>
>>3) Is there any research group trying to converge both approaches?
>>
>>Best Regards,
>
>  and my reply was below:
>
> For your question 3), I have no idea. For question 1) I can't say I've
> ever heard of anyone talk about this. For question 2), I imagine the
> answer is yes, although the boundaries between "what's Alife" and
> "what's program learning" (for example) may be blurry.
>
> So, imagine, for example, a population of many different species of
> "neurons" (or should I call them automata? or maybe I should call them
> "virtual ants"?) Most of the individuals have only a few "friends" (a
> narrow social circle) -- the "friendship" relationship can be viewed
> as an "axon-dendrite" connection -- these friendships are semi-stable;
> they evolve over time, and the type & quality of information exchanged
> in a friendship also varies. Is a social network of friends able to
> solve complex problems? The answer is seemingly yes, if the
> individuals are digital models of neurons. (To carry analogy further:
> different species of individuals would be analogous to different types
> of neurons e.g. purkinje cells vs pyramid cells vs granular vs. motor
> neurons. Individuals from one species may tend to be very gregarious,
> while those from other species might be generally xenophobic. etc.)
>
> I have no clue if anyone has ever explored genetic algorithms or
> related alife algos, factored together with the individuals being
> involved in a social network (with actual information exchange between
> friends). No clue as to how natural/artificial selection should work.
> Do anti-social individuals have a possibly redeeming role w.r.t. the
> organism as a whole? Do selection pressures on individuals (weak
> individuals are cullled) destroy social networks? Do such networks
> automatically evolve altruism, because a working social network with
> weak, altruistically-supported individuals is better than a shredded,
> dysfunctional social network consisting of only strong individuals?
> Dunno. Seems like there could be many many interesting questions.
>
> I'd be curious about the answers to Antonio's questions ...
>
> --linas
>
>
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> agi
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