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Diagram: Fitness Landscape

Fitness Landscape

A fitness landscape is a concept that employs the metaphor of a physical landscape to depict more or less 'fit' regions of phase space.

Related Terms and Topics: Fitness Peaks, basins-of-attractions, critical-point, Tipping Points, Phase Space


A fitness landscape is not a physical space. It is a way of describing the range of all possible behaviors open to a system, or its Phase Space. Agents within a Complex System may have the capacity to behave in a wide variety of ways, but some of these are more efficient than others. The landscape is a metaphoric mapping of how well different states within a system's degrees of freedom perform. We picture the fitness landscape as being composed of a series of hilly plateaus of different heights.  This performance is measured as Fitness, with more 'fit' states being mapped higher within the landscape, or as Fitness Peaks.

That said peaks within the fitness landscape are not static, but change over time.

Again, it may be helpful to illustrate with an example

Example: At one point, Detroit was a 'fit' site for gaining employment, due to the auto-industry. Subsequently, with shifting global production trends, the forces that made Detroit 'fit' altered, and its 'peak' within the landscape of potential employment gradually eroded.

The interesting about a fitness landscape is that there are multiple peaks. We can think of these as multiple niches that are ripe for inhabitation. Different species can pursue different survival strategies to fill these niches. Some strategies can support a large population of species (think of this as a broad and tall hill). Others may able to eke out an existence, but their niche may only support a small number of species. This peak might be equally tall, but would be narrower.

The idea of a fitness landscape serves to illustrate the broader concept of Fitness within a Complex System.

This is tantamount to a system's Degrees of Freedom.


Exploration or Exploitation

It is very interesting to think about how best to explore a fitness landscape.

Imagine that you camping in a hilly landscape, without a map, and you plan to go for a hike. It is morning on a cloudy day, and you can see different foothills around, you, but due to the cloud cover you can't see the tops of the hills The sun is expected to break through later in the afternoon and you want to find yourself on the tallest peak with the "fittest" or best view. You begin to wander randomly  and make a decision that you will follow whatever pathways seem to be taking you higher at each step. After many hours of wandering, you find yourself on a plateau where you cannot move further without your footsteps taking you down. You stop there, have a drink, and wait for the sun to come out. When it does, you realize that you are at the top of a hill, but that, in the distance, are other hills with taller peaks. You climbed to a local optima, but your random steps failed to take you to the global optima within the landscape. You became trapped on the peak you selected at the start. 

Unfortunately, in this scenario, while you were able to explore part of the landscape, you did not get an adequate overview of the situation to choose that section of landscape well.

There are a number of ways to help solve this problem, and this can be done using an exploration  strategy called "simulated annealing". Simulated annealing combines broad exploration at the start of an exploration sequence, with more focused exploration at the end of an exploration of a sequence. 


 


Cite this page:

Wohl, S. (2022, 6 June). Fitness Landscape. Retrieved from https://kapalicarsi.wittmeyer.io/definition/fitness-landscape

Fitness Landscape was updated June 6th, 2022.

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Santa Fe Institute; Fitness Landscape

Major complexity theorist associated with the Sante Fe institute, developed idea of a Fitness Landscape

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Fitness Landscapes

Fitness Landscapes / Path Analysis Learn more →

epigenesis

Caramelization half and half robust kopi-luwak, brewed, foam affogato grounds extraction plunger pot, bar single shot froth eu shop latte et, chicory, steamed seasonal grounds dark organic. Learn more →

This is a list of Terms that Fitness Landscape is related to.

A regime of particular fitness that an agent can occupy.

Fitness ‘peaks’ are regimes wherein a given agent behavior maximizes energetic returns while minimizing outputs. Peaks are thus optimum behaviors in phase space - though there may be numerous peaks, each employing different strategies. See also {{Fitness-Landscape}} Learn more →

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Short video illustrating Conrad Waddington's Epigenetic Landscape

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This is a list of Urban Fields that Fitness Landscape is related to.

This is a list of Key Concepts that Fitness Landscape is related to.

A tipping point (often referred to as a 'critical point') is a threshold within a system where the system shifts from manifesting one set of qualities to another.

Complex systems do not follow linear, predictable chains of cause and effect. Instead, system trajectories can diverge wildly into entirely different regimes.

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Complex Adaptive Systems become more 'fit' over time. Depending on the system, Fitness can take many forms,  but all involve states that achieve more while expending less energy.

What do we mean when we speak of Fitness? For ants, fitness might be discovering a source of food that is abundant and easy to reach. For a city, fitness might be moving the maximum number of people in the minimum amount of time. But fitness criteria can also vary - what might be fit for one agent isn't necessarily fit for all.

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Complex Systems can unfold in multiple trajectories. However, there may be trajectories that are more stable or 'fit'. Such states are considered 'attractor states'.

Complex Adaptive Systems do not obey predictable, linear trajectories. They are "Sensitive to Initial Conditions", such that small changes in these conditions can lead the system to unfold in unexpected ways. That said, in some systems, particular 'potential unfoldings' are more likely to occur than others. We can think of these as 'attractor states' to which a system will tend to gravitate.

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There would be some thought experiments here.

Navigating Complexity © 2015-2024 Sharon Wohl, all rights reserved. Developed by Sean Wittmeyer
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