Some other evo models
This simulation looks interesting, but I haven’t had time to explore
it in any detail. From the home page:
PolyWorld is a computational ecology that I developed to explore issues
Life. Simulated organisms reproduce sexually, fight and kill and
eat each other, eat the food that grows throughout the world, and either
develop successful strategies for survival or die. An organism's entire
behavioral suite (move, turn, attack, eat, mate, light) is controlled
by its neural network "brain". Each brain's architecture--it's
neural wiring diagram--is determined from its genetic code, in terms
of number, size, and composition of neural clusters (excitatory and
inhibitory neurons) and the types of connections between those clusters
(connection density and topological mapping). Synaptic efficacy is modulated
via Hebbian learning, so, in principle, the organisms have the ability
to learn during the course of their lifetimes. The organisms perceive
their world through a sense of vision, provided by a computer graphic
rendering of the world from each organism's point of view. The organisms'
physiologies are also encoded genetically, so both brain and body, and
thus all components of behavior, evolve over multiple generations. A
variety of "species", with varying individual and group survival
strategies have emerged in various simulations, displaying such complex
ethological behaviors as swarming/flocking, foraging, and attack avoidance.
Another potentially interesting package that I haven’t had time
to explore yet.
This is perhaps the tightest evo simulator out there, on the order
of 300 lines of code. It allows some control of interesting variables,
but because of the huge default (and unchangeable) world size is painfully
slow. It also provides a minimum of interesting data output.
This is an interesting simulation that has artificial agents (“ants”)
equipped with sensors, motor capabilities, and neural nets. It was written
as an undergraduate thesis project. Unfortunately, the author (now a
grad student in CS) implemented only a sort of group selection model,
and thus it is unsuitable for studying most interesting questions in