Imitating biology

[lee_merrill]

Source: Evolution News

Source

© Copyright Original Source

Lots of designs!

Source: Evolution News

... these are great

© Copyright Original Source

Designs we try an imitate are not what you would expect if nature is cobbled together with an algorithm that seeks local optimums.

Blessings,
Lee

[shunyadragon]

Bad start citing Inelligent Design literature in the guise of science.

[Stoic]

Source: Evolution News

Source

© Copyright Original Source

Lots of designs!

Source: Evolution News

... these are great

© Copyright Original Source

Designs we try an imitate are not what you would expect if nature is cobbled together with an algorithm that seeks local optimums.

Nature has had billions of years of trial and error to come up with some nice designs. It would be silly not to take advantage of all that R & D.

[lee_merrill]

Nature has had billions of years of trial and error to come up with some nice designs. It would be silly not to take advantage of all that R & D.

Yet inelegant design examples (such as the human retina) are often pointed to as examples of what we should expect from evolution.

Blessings,
Lee

[shunyadragon]

Yet inelegant design examples (such as the human retina) are often pointed to as examples of what we should expect from evolution.

Blessings,
Lee

The evolutio of the eye of various forms, and the retina have been demonstrated to have been capable of being evolved naturally. Your attempting to propose a negative hypothesis which cannot be falsified.

[shunyadragon]

Yet inelegant design examples (such as the human retina) are often pointed to as examples of what we should expect from evolution.

Blessings,
Lee

The evolution of the eye of various forms, and the retina have been demonstrated to have been capable of being evolved naturally from the simple to the complex. Your attempting to propose a negative hypothesis which cannot be falsified.

[Stoic]

Yet inelegant design examples (such as the human retina) are often pointed to as examples of what we should expect from evolution.

I believe the argument is that such inelegant design examples are what we would not expect from an omniscient, omnipotent God, rather than that is all we can expect from evolution.

[Starlight]

Designs we try an imitate are not what you would expect if nature is cobbled together with an algorithm that seeks local optimums.

For the most part when we look at the designs of biological systems, they seem to be pretty terrible in terms of design quality. But a small number of them are good designs.

This is what we would expect from chance and evolution - a statistical distribution of design quality centered around poorer designs. Absolutely not what we would expect from an intelligent being doing the designing.

[Leonhard]

Yet inelegant design examples (such as the human retina) are often pointed to as examples of what we should expect from evolution.

True, but you're missing that there's clear evidence of lineage and inheritance of this mistake. A designer can for any arbitrary reasons do something different, he is not tied down by past mistakes. Yet we see biological features inherited as clear as day and shared back up to a common ancestor, but then not with species outside of this common ancestor. So it is explained by evolution, but it is left a mystery if it is a designer.

Why would a designer choose to design things, so it matches the patterns of inheritance we'd see if things naturally evolved?

[rossum]

Yet inelegant design examples (such as the human retina) are often pointed to as examples of what we should expect from evolution.

Inelegant design examples are contrasted with better design examples, such as the cephalopod retina, to counter the design hypothesis. Why does the designer use both a better design and a worse design? Is the hypothesised designer incapable of telling good design from bad design?

[TheLurch]

Designs we try an imitate are not what you would expect if nature is cobbled together with an algorithm that seeks local optimums.

Why would that be true? Both aspects of the statement - one that evolution only discovers local optima, and two that we'd only ever seek to imitate global optima - need to be explained.

[lee_merrill]

For the most part when we look at the designs of biological systems, they seem to be pretty terrible in terms of design quality. But a small number of them are good designs.

I would disagree, design quality seems to be good overall. What terrible designs did you have in mind?

Why would a designer choose to design things, so it matches the patterns of inheritance we'd see if things naturally evolved?

Common design patterns, would be the reasoning here.

Why does the designer use both a better design and a worse design?

Both designs are good, apparently, both retinas have their own rationale:

Source: Reasons to Believe

Source

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Blessings,
Lee

[lee_merrill]

Why would that be true? Both aspects of the statement - one that evolution only discovers local optima, and two that we'd only ever seek to imitate global optima - need to be explained.

Evolution is a hill-climbing algorithm, so it will tend to stop at the top of the nearest hill.

Source: Towards Data Science

One of the main problems faced by evolutionary algorithms is the presence of local optima in the fitness landscape. Local optima, can, in fact, mislead our algorithm to not reach our desired global maxima in favour of a less optimal solution.

Source

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Now he goes on to describe ways to alleviate this problem, but it's still a problem.

And I don't claim that we seek only to imitate global optimums, I only claim that biological designs are remarkably good, better even than humans have been able to do, in various cases.

Blessings,
Lee

[TheLurch]

Evolution is a hill-climbing algorithm, so it will tend to stop at the top of the nearest hill.

Source: Towards Data Science

One of the main problems faced by evolutionary algorithms is the presence of local optima in the fitness landscape. Local optima, can, in fact, mislead our algorithm to not reach our desired global maxima in favour of a less optimal solution.

Source

© Copyright Original Source

Now he goes on to describe ways to alleviate this problem, but it's still a problem.

And I don't claim that we seek only to imitate global optimums, I only claim that biological designs are remarkably good, better even than humans have been able to do, in various cases.

That's an evolutionary algorithm. it's not evolution. Try again.

[shunyadragon]

Evolution is a hill-climbing algorithm, so it will tend to stop at the top of the nearest hill.

Source: Towards Data Science

One of the main problems faced by evolutionary algorithms is the presence of local optima in the fitness landscape. Local optima, can, in fact, mislead our algorithm to not reach our desired global maxima in favour of a less optimal solution.

Source

© Copyright Original Source

Now he goes on to describe ways to alleviate this problem, but it's still a problem.

And I don't claim that we seek only to imitate global optimums, I only claim that biological designs are remarkably good, better even than humans have been able to do, in various cases.

Blessings,
Lee

Hill? Are you referring to an energy hill. You need to clarify this, because there is more energy availble than necessary for evolution. Evolution is i a nillion hills and still climbing.

The bottom line is this is not a scientific approach.