Simulating Evolution Robbie Rosati

Definition of Evolution “The change in heritable traits in biological populations over generations.” – Wikipedia NOT: adaptation within a generation, improvement toward a predetermined goal

Mechanisms of Evolution Natural selection repeated trial and error Genetic drift genetic selection bias At what level do these happen?

Genetic Drift

Unit of Selection Natural selection: genes Genetic drift: function of population size

“Selfish” Gene Selection The genes that are passed on serve their own interest (replication) by giving the organism beneficial traits. Organisms are “survival machines” for their genes. Genes can reproduce at the expense of the organism. Ex. Maternal flour beetle gene that causes the death of embryos that do not inherit the gene. Ex. Mating behavior of some spiders, praying mantises

Limits of Natural Selection Lack of necessary genetic diversity Non-fatal mutations tend to be small - Developmental history important

Genetic Algorithms Mimic the process of natural selection Sort-of subject to the same constraints Anecdotes

Evolutionarily Stable Strategies If a population behaves with an ESS, it is resistant to invasion by mutant strategies similar to Nash equilibrium

Hawk-Dove game Similar to Prisoner's Dilemma, different payoff matrix.

The Prisoner's Dilemma Two members of a criminal gang are arrested and imprisoned. Each prisoner is in solitary confinement with no means of speaking to or exchanging messages with the other. The prosecutors don't have enough evidence to put both prisoners away for more than a few months, so they make them an offer: If A and B each betray the other, each of them serves 8 years in prison If A betrays B but B remains silent, A will be set free and B will serve 20 years in prison (and vice versa) If A and B both remain silent, both of them will only serve 6 months in prison.

E(C) = (3+0)/2 = 3/2 E(D) = (5+1)/2 = 3

Iterated Prisoner's Dilemma Indefinite length Players remember past rounds, adjust strategy Requires mutual cooperation to have the highest total reward

Axelrod and Hamilton (1981) Performed IPD simulations at University of Maryland Asked economists, sociologists, physicists, etc to mail in strategies

Tournaments Initial tournament of 14 strategies – 200 rounds Second: 62 strategies – 200 rounds Third: “ecological tournament” – 1000 rounds Winners: Tit-for-tat, every time Observations: no ESS

Recent Recreation http://codegolf.stackexchange.com/questions/2357/

Conway's Game of Life (1970)

Game of Life Examples Turing-complete First self-replicating pattern created 2010 First self-replicating pattern to preserve its instruction tape created 2013

Biogenesis http://biogenesis.sourceforce.org GREEN: gets energy from the Sun, coverts CO2 into O2 RED: allows eating other organisms CYAN: allows movement in stick direction YELLOW: increases number of children made when reproducing WHITE: infects any organism so that it's next child has the owner of the white segment's genes, costs energy GREY: kills on contact, costs energy BLUE: shield against RED, WHITE, and GREY

Critterding Critters are informed by sensors: If their head is touches a food cube If their head touches another critter If they are able to procreate About their energy state About their age About the state of their joints What the world looks like (8x8 pixel RGBA vision) Critters can make use of the following motor neurons (actions): Bend joint (in two directions) Eat procreate

Related projects BrainInWorld: neural-net organism simulator written by a physicist at Fermilab: https://github.com/souvik1982/Brain OpenWorm (http://openworm.org): attempt to simulate a C. elegans nematode entirely in software Framsticks (http://www.framsticks.com) : 3D artificial life simulator, more elaborate than Critterding