An Introduction to Genetic Algorithms - Boente

Chapter 3: Genetic Algorithms in Scientific Models
Like many of the other models we have looked at, Echo is meant to be as simple as possible while still
capturing essential aspects of ecological systems. It is not meant to model any particular ecosystem (although
more detailed versions might someday be used to do so); it is meant to capture general properties common to
all ecosystems. It is intended to be a platform for controlled experiments that can reveal how changes in the
model and in its parameters affect phenomena such as the relative abundance of different species, the
development and stability of food webs, conditions for and times to extinction, and the evolution of symbiotic
communities of organisms.
Echo's world—a two−dimensional lattice of sites—contains several different types of "resources," represented
in the model by letters of the alphabet. These can be thought of as potential sources of energy for the
organisms. Different types of resources appear in varying amounts at different sites.
The world is populated by "agents," similar in some ways to the agents in the ERL model. Each agent has a
genotype and a phenotype. The genotype encodes a set of rules that govern the types and quantities of
resources the agent needs to live and reproduce, the types and quantities of resources the agent can take up
from the environment, how the agent will interact with other agents, and some physical characteristics of the
agent that are visible to other agents. The phenotype is the agent's resulting behavior and physical appearance
(the latter is represented as a bit pattern). As in the ERL model, each agent has an internal energy store where
it hoards the resources it takes from the environment and from other agents. An agent uses up its stored energy
when it moves, when it interacts with other agents, and even when it is simply sitting still (there is a
"metabolic tax" for just existing). An agent can reproduce when it has enough energy stored up to create a
copy of its genome. If its energy store goes below a certain threshold, the agent dies, and its remaining
resources are returned to the site at which it lived.
At each time step, agents living at the same site encounter one another at random. There are three different
types of interactions they can have:combat, trade, and mating. (An Echo wag once remarked that these are the
three elements of a good marriage.) When two agents meet, they decide which type of interaction to have on
the basis of their own internal rules and the outward physical appearance of the other agent. If they engage in
combat, the outcome is decided by the rules encoded in the genomes of the agents. The loser dies, and all its
stored resources are added to the winner's store.
If the two agents are less warlike and more commercial, they can agree to trade. An agent's decision to trade is
again made on the basis of its internal rules and the other agent's external appearance. Agents trade any stored
resources in excess of what they need to reproduce. In Echo an agent has the possibility to evolve
deception—it might look on the outside as though it has something good to trade whereas it actually has
nothing. This can result in other agents' getting "fleeced" unless they evolve the capacity (via internal rules) to
recognize cheaters.
Finally, for more amorous agents, mating is a possibility. The decision to mate is, like combat and trade,
based on an agent's internal rules and the external appearance of the potential mate. If two agents decide to
mate, their chromosomes are combined via two−point crossover to form two offspring, which then replace
their parents at the given site. (After reproducing, the parents die.)
If an agent lives through a time step without gaining any resources, it gives up its current site and moves on to
another nearby site (picked at random), hoping for greener pastures.
The three types of interactions are meant to be idealized versions of the basic types of interactions between
organisms that occur in nature. They are more extensive than the types of interactions in any of the case
studies we have looked at so far. The possibilities for complex interactions, the spatial aspects of the system,
and the separation between genotype and phenotype give Echo the potential to capture some very interesting
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