Evolving hominins in HomininSpace– genetic algorithms and the search for the perfect Neanderthal
Fulco Scherjon
Abstract Genetic Algorithms (GA) are evolutionary computational techniques inspired by natural selection in which individuals participate in a search for optimal results. HomininSpace (HS) is a large scale realistic agent-based modelling and simulation system exploring hominin dispersal through reconstructed landscapes in the deep past. A case study in HS implements Neanderthals moving through North-west Europe where simulated presence is scored against radiometrically dated archaeological sites (checkpoints). Model parameters influence agent behavior and GA are implemented in an automated scan for that specific parameter combination that produces a Neanderthal agent that best matches the archaeology.
The underlying research question for the implementation of HS is the characterization of the effects of the different parameters on hominin behavior in the landscape. 6000 simulations were run with randomly constructed parameter combinations. Statistical analysis (principal components analysis and cluster analysis) are used to determine the influence of each parameter in simulations with high scores. But the total dimensions of the parameter space (23 parameters) is simply too large for an exhaustive parameter sweep guaranteed to find the perfect Neanderthal.
In an effort to optimize that search GA techniques are applied against the set of simulated parameter combinations and their simulation results. Each unique combination of parameter settings is taken as an individual that participates in the automated search. Tournaments are organized to select high potentials, and randomly mixed pairs of successful parents produce hopefully more successful offspring (new combinations). Better scoring individuals are also point mutated on a single parameter to create even more new combinations. Simulation results for the new parameter combinations are added to the pool of individuals that participate in the following tournament rounds. This paper presents the preliminary results and the characterization of some very good Neanderthals.
