i.e. individual-based versus ecosystem-based (cf waves) problem solving. However, we have not looked at problem solving together.

If we look at ecosystems (link) it is clear that there are specialistic individuals, but they cannot do things alone. So the question becomes: is cooperative problem solving easy?

in the ligase system there was no evolution (i.e. predefined). If we put it in, is it stable?

Focusing on ecosystems:

most population models don't take conservation of mass into account.

and just being there is neglected, while it should be considered in terms of generating new niches through garbage, energy transduction, information transduction (processing of sunlight). There is no magic coat to be invisible.

probably all considerations of diversity in ecosystems are flawed because this is not take seriously.

In an artificial system however, we can phrase this problem in an interesting way, while in biology that is often not that clear. For this end Folkert de Boer and P. Hogeweg developed a function optimizing model in the following way:

cf. Pagie and Hogeweg (REF) they developed a LISP program which would solve a complex polynomial, where we as we have seen, populations can integrate information over generations.

So far we have been exploring the idea that space is important for
- clever individuals; population based diversity
- but also for populaiton based competition

i.e.:
INDIVIDUAL BASED vs ECOSYSTEM-BASED (cf waves) "PROBLEM SOLVING"

However we have not looked at problem solving TOGETHER.

Ecosystem: special individuals but they cannot do things alone:
Q: is cooperative problem solving easy?
-In the Hypercycle: cooperative entities together get more information: cooperative solution, population-based diversity
-ligase system: didn't evolve, Q: if we put it in it is stable? (i.e. predefined)

Notes:
- most population models don't take conservation of mass into account
- neglect JUST BEING THERE creates a new niche: garbage, digestion, energy transduction, information transduction (processing of sunlight) (NO MAGIC COAT TO BE INVISIBLE)
- all considerations of diversity in ecosystems are flawed because this is not taken seriously

In artificial system can phrase problem in interesting way (in Biology often not that clear!)

MODEL (FOLKERT AND PAULIEN)
- solving polynomial using LISP etc. (cf Pagie Hogeweg): yes can integrate information over generations to solve as we have seen.
Q: can it evolve individual-based or population-based (co-operation) (vs. what is more stable?)

Plane 1:
- prey - <x,y> co-ordinates
- predators evolve LISP function f(x,y) to solve predefined polynomial F(x,y)
Plane 2:
- detritus: left-overs from predation <c> = F(x,y) - f(x,y)
- detritus eater: evolves function to match left-overs g(x,y)

-predators and detritus don't see each other and only detritus eater sees detritus.

Results:
- waves of high x values through field of low x values: speciation in prey
- evolution: spreads out low x, high y to low x y etc etc (movies of speciation) to different corners of x,y plane.
Types of solutions:
- very nice solutions!
- very nice partitioning of polynomial between predator and detritus eater
- first population based diverity
- then super beast takes over and detritus eater dies out
- relative to information threshold: go for population based solution!

TODO List

## Ecosystem based problem solving

So far we have been exploring the idea that space is important for:

- clever individuals and population-based diversity
- but also for population-based competition (group-selection?)

i.e. individual-based versus ecosystem-based (cf waves)problem solving. However, we have not looked at problem solvingtogether.If we look at ecosystems (link) it is clear that there are specialistic individuals, but they cannot do things alone. So the question becomes:

is cooperative problem solving easy?If we put it in, is it stable?Focusing on ecosystems:

conservation of massinto account.just being thereis neglected, while it should be considered in terms of generating new niches through garbage, energy transduction, information transduction (processing of sunlight).There is no magic coat to be invisible.In an artificial system however, we can phrase this problem in an interesting way, while in biology that is often not that clear. For this end Folkert de Boer and P. Hogeweg developed a function optimizing model in the following way:

can it evolve individual-based or population-based (co-operation) and what is more stable?The model:

The results of this model show:

## References

Work by Folkert

COURSE 2006-2007

So far we have been exploring the idea that space is important for

- clever individuals; population based diversity

- but also for populaiton based competition

i.e.:

INDIVIDUAL BASED vs ECOSYSTEM-BASED (cf waves) "PROBLEM SOLVING"

However we have not looked at problem solving TOGETHER.

Ecosystem: special individuals but they cannot do things alone:

Q: is cooperative problem solving easy?

-In the Hypercycle: cooperative entities together get more information: cooperative solution, population-based diversity

-ligase system: didn't evolve, Q: if we put it in it is stable? (i.e. predefined)

Notes:

- most population models don't take conservation of mass into account

- neglect JUST BEING THERE creates a new niche: garbage, digestion, energy transduction, information transduction (processing of sunlight) (NO MAGIC COAT TO BE INVISIBLE)

- all considerations of diversity in ecosystems are flawed because this is not taken seriously

In artificial system can phrase problem in interesting way (in Biology often not that clear!)

MODEL (FOLKERT AND PAULIEN)

- solving polynomial using LISP etc. (cf Pagie Hogeweg): yes can integrate information over generations to solve as we have seen.

Q: can it evolve individual-based or population-based (co-operation) (vs. what is more stable?)

Plane 1:

- prey - <x,y> co-ordinates

- predators evolve LISP function f(x,y) to solve predefined polynomial F(x,y)

Plane 2:

- detritus: left-overs from predation <c> = F(x,y) - f(x,y)

- detritus eater: evolves function to match left-overs g(x,y)

-predators and detritus don't see each other and only detritus eater sees detritus.

Results:

- waves of high x values through field of low x values: speciation in prey

- evolution: spreads out low x, high y to low x y etc etc (movies of speciation) to different corners of x,y plane.

Types of solutions:

- very nice solutions!

- very nice partitioning of polynomial between predator and detritus eater

- first population based diverity

- then super beast takes over and detritus eater dies out

- relative to information threshold: go for population based solution!