James Winters

@replicatedtypo.bsky.social

1321 Followers 725 Following

Simulating sci-fi novels and calling it cultural evolution Centre for Culture and Evolution | Brunel University London | https://j-winters.github.io

Selected simulation runs showing a range of dynamics. Coloured lines represent the complexity of technological systems (denoted with η) and search spaces (denoted with λ) for different simulation runs. Several simulation runs show accelerated growth in the complexity of technological systems. This includes: η=0.80, λ=0.80; η=0.95, λ=0.95; η=0.95, λ=0.99; η=0.99, λ=0.95. As one parameter or the other decreases, the dynamics slow down and show less potential for accelerated growth, e.g., η=0.99, λ=0.10; η=0.95, λ=0.05. And some simulation runs fail to exhibit any open-ended or accelerated growth, i.e., η=0.10, λ=0.99; η=0.99, λ=0.99.
A heatmap showing the average complexity of technological systems for all simulation runs across η and λ at the end of the simulation. It shows the average complexity of is low for most regions of the parameter space, but it increases as η and λ approach 1.0. The regions with highest complexity are when η=0.95 and λ=0.80 and when η=0.90 and λ=0.95.
All simulation runs (coloured lines) showing the complexity for technological systems (y-axis) for η=0.01 and λ=0.01 over generations (x-axis). When η=λ=0.01, none of the runs manage to survive for the full 10,000 generations and are restricted to relatively simple technological systems.
A diagram outlining the general dynamics of bitw0r1d. At each generation, a society needs to find effective mappings between 𝕋 and 𝕊. The effectiveness of this mapping as well as the complexity of 𝕋 and 𝕊 determine the amount of resources (R). These resources are then allocated to two processes: one which changes the technological systems of a society and another which changes the underlying search space. We assume both processes follow a two-step cultural evolutionary dynamic of generating and adopting changes. Our model varies the selection pressures on 𝕋 and 𝕊 by manipulating the extent to which the adoption of changes are stochastic or deterministic: η controls the selection pressures on 𝕋 and λ controls the selection pressures on 𝕊.