Evolution in varying environments : rapid emergence of modular systems

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Nadav Kashtan",
  title =        "Evolution in varying environments : rapid emergence of
                 modular systems",
  school =       "Weizmann Institute of Science",
  year =         "2008",
  address =      "Israel",
  month =        mar,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://lib-phds1.weizmann.ac.il/Dissertations/Kashtan_Nadav.pdf",
  size =         "107 pages",
  abstract =     "The design of biological systems is shaped by
                 evolution. There are several general features of
                 biological design that seem to occur again and again
                 across levels of biological organisation. One such
                 central feature is modularity, biological systems can
                 often be decomposed into nearly independent subsystems.
                 Modularity can be seen on several levels, from the
                 design of organisms (tissues, limbs, sensory organs),
                 through the design of regulatory networks in the cell
                 (signalling pathways, transcription modules) and down
                 to the design of many bio-molecules (protein domains).
                 Despite its presence on all of these levels, the
                 evolutionary origin of modularity is currently
                 considered as an open question.

                 The first part of my Ph.D. research aimed at
                 understanding the evolutionary origin of modularity. We
                 used computer simulations that mimic natural evolution
                 to study the evolution of simple model systems such as
                 Logic circuits, neural networks and RNA secondary
                 structure. We find that evolution under constant goals
                 (i.e. that do no change over time) typically lead to
                 highly optimal systems with non-modular structure. In
                 contrast, we find that evolution under environments
                 that change over time in a modular fashion, such that
                 each new goal is a different combination of the same
                 set of subgoals, lead to the spontaneous emergence of
                 modularity and network motifs. The evolved systems
                 developed a specific module for each of the sub goals.
                 Although sub-optimal the modular systems were able to
                 adapt rapidly when the environment changed. We suggest
                 that such switching between related goals may represent
                 biological evolution in a changing environment that
                 requires, at different times or conditions, different
                 combinations of the same set of basic biological
                 functions (such as eating, moving, and mating). This
                 study therefore may help to explain some of the
                 evolutionary forces that promote structural simplicity
                 in biological systems.

                 A second well-known puzzle which is known in evolution
                 studies is whether the theory can explain the speed at
                 which the present complexity of life evolved. My second
                 research objective was to try to find mechanisms,
                 compatible with natural evolution, which can speed up
                 evolution. We studied the effect of varying
                 environments on the speed of evolution, defined as the
                 number of generations needed for an initially random
                 population to achieve a given goal. We find that
                 varying environments can dramatically speed up
                 evolution compared to evolution in constant
                 environment. A consistent speedup was found under
                 modularly varying goals. Importantly, we find that the
                 speedup scales with the complexity of the goal: the
                 harder the goals the larger the speedup. This study
                 suggests that varying environments might significantly
                 contribute to the speed of natural evolution. In
                 addition, it suggests a way to accelerate optimisation
                 algorithms and improve evolutionary approaches in

                 We then tried to understand the underlying reasons for
                 the observed speedup. We suggested a simple
                 mathematical model that can be solved analytically.
                 This model seems to explain the reasons for a rapid
                 evolution of modular structures under modularly varying
                 goals. It helps us understand the effects found in
                 simulations of more complex systems described above.",
  abstract =     "In the last part of my research we studied the effects
                 of extinctions in a spatially distributed environment.
                 We demonstrate that extinctions can impact the design
                 of evolved organisms. Specifically, extinctions in
                 heterogeneous environment lead to the emergence of
                 modular species. This is because modular species can
                 better adapt when they encounter niches freed by
                 extinction events. We further show how lack of
                 extinctions tends to result in distinct specialist
                 species in each niche, whereas extinctions lead to
                 formation of multi-niche species with modular and
                 evolvable design.

                 In summary, this thesis has extended our understanding
                 of the role of varying environments in generating
                 biological structure and in speeding up evolution. It
                 used detailed simulations and analytical models to test
                 hypothesis, rather than the more commonly used method
                 of well-argued prose. The main idea is that over time,
                 organisms learn, in their genome, the shared subgoals
                 common to different environments, and evolve modules to
                 solve these different subgoals. This modular design
                 makes it much easier to rewire and adapt when
                 environments change. The present results also suggest
                 new ways to accelerate optimization algorithms, and
                 open the way to studying additional relationships
                 between environmental variation and biological
  notes =        "MOLECULAR CELL BIOLOGY Supervisor: Uri Alon

                 chapter 1 \cite{Kashtan:2005:PNAS} chapter 2

                 In english.",

Genetic Programming entries for Nadav Kashtan