https://www.nature.com/articles/s42256-020-00278-8

Abstract
Evolutionary computation is inspired by the mechanisms of biological
evolution. With algorithmic improvements and increasing computing
resources, evolutionary computation has discovered creative and
innovative solutions to challenging practical problems. This paper
evaluates how today’s evolutionary computation compares to biological
evolution and how it may fall short. A small number of well-accepted
characteristics of biological evolution are considered: openendedness,
major transitions in organizational structure, neutrality and genetic
drift, multi-objectivity, complex genotype-to-phenotype mappings and
co-evolution. Evolutionary computation exhibits many of these to some
extent but more can be achieved by scaling up with available computing
and by emulating biology more carefully. In particular, evolutionary
computation diverges from biological evolution in three key respects: it
is based on small populations and strong selection; it typically uses
direct genotype-to-phenotype mappings; and it does not achieve major
organizational transitions. These shortcomings suggest a roadmap for
future evolutionary computation research, and point to gaps in our
understanding of how biology discovers major transitions. Advances in
these areas can lead to evolutionary computation that approaches the
complexity and flexibility of biology, and can serve as an executable
model of biological processes.

On 4/13/23 1:46 AM, Popping Mad wrote:
> https://www.nature.com/articles/s42256-020-00278-8
>
> Abstract
> Evolutionary computation is inspired by the mechanisms of biological
> evolution. With algorithmic improvements and increasing computing
> resources, evolutionary computation has discovered creative and
> innovative solutions to challenging practical problems. This paper
> evaluates how today’s evolutionary computation compares to biological
> evolution and how it may fall short. A small number of well-accepted
> characteristics of biological evolution are considered: openendedness,
> major transitions in organizational structure, neutrality and genetic
> drift, multi-objectivity, complex genotype-to-phenotype mappings and
> co-evolution. Evolutionary computation exhibits many of these to some
> extent but more can be achieved by scaling up with available computing
> and by emulating biology more carefully. In particular, evolutionary
> computation diverges from biological evolution in three key respects: it
> is based on small populations and strong selection; it typically uses
> direct genotype-to-phenotype mappings; and it does not achieve major
> organizational transitions. These shortcomings suggest a roadmap for
> future evolutionary computation research, and point to gaps in our
> understanding of how biology discovers major transitions. Advances in
> these areas can lead to evolutionary computation that approaches the
> complexity and flexibility of biology, and can serve as an executable
> model of biological processes.

This does not seem very relevant to paleontology or even to systematics.

On 4/13/23 08:51, John Harshman wrote:
> This does not seem very relevant to paleontology or even to systematics.

You have a bit to learn. There is no such thing as systematics. There
is only computational biology and biologial statistics.

On 4/13/23 8:35 PM, Popping Mad wrote:
> On 4/13/23 08:51, John Harshman wrote:
>> This does not seem very relevant to paleontology or even to systematics.
>
>
> You have a bit to learn. There is no such thing as systematics. There
> is only computational biology and biologial statistics.

!

John Harshman <john.harshman@gmail.com> wrote:
> On 4/13/23 8:35 PM, Popping Mad wrote:
>> On 4/13/23 08:51, John Harshman wrote:
>>> This does not seem very relevant to paleontology or even to systematics.
>>
>>
>> You have a bit to learn. There is no such thing as systematics. There
>> is only computational biology and biologial statistics.
>
> !

Don't be suprised. I don't know what this resistence is in the Paleo
community to hard math and Balesyain statistics.

All evolutionary theory can be reduced to mathmatical alorithms with
maps. I sort of giggled when I read current commentary on AI
applications. There is a failure to understand what AI does and where
the current state of the art is.

The future of Paleo is just like it is for the rest of Biology, it is
computational mathmatics. The same allgorthism used to describe
econological problems and microbiology are also applicable to
evolutionary problems and Paleontology.

This is especially true as most geneitics is available.

On 4/14/23 9:16 AM, Ruben Safir wrote:
> John Harshman <john.harshman@gmail.com> wrote:
>> On 4/13/23 8:35 PM, Popping Mad wrote:
>>> On 4/13/23 08:51, John Harshman wrote:
>>>> This does not seem very relevant to paleontology or even to systematics.
>>>
>>>
>>> You have a bit to learn. There is no such thing as systematics. There
>>> is only computational biology and biologial statistics.
>>
>> !
>
>
> Don't be suprised. I don't know what this resistence is in the Paleo
> community to hard math and Balesyain statistics.

There is no such resistance. But your citation isn't relevant to
paleontology. (I'm assuming you mean "Bayesian"?)

> All evolutionary theory can be reduced to mathmatical alorithms with
> maps. I sort of giggled when I read current commentary on AI
> applications. There is a failure to understand what AI does and where
> the current state of the art is.
>
> The future of Paleo is just like it is for the rest of Biology, it is
> computational mathmatics. The same allgorthism used to describe
> econological problems and microbiology are also applicable to
> evolutionary problems and Paleontology.
>
> This is especially true as most geneitics is available.

??

On 4/14/23 17:47, John Harshman wrote:
>
> There is no such resistance. But your citation isn't relevant to
> paleontology.

OK perhaps I made an error

On 4/14/23 4:10 PM, Popping Mad wrote:
> On 4/14/23 17:47, John Harshman wrote:
>>
>> There is no such resistance. But your citation isn't relevant to
>> paleontology.
>
>
> OK perhaps I made an error

!!