This thesis investigates the problem solving capabilities of Probabilistic Plushies.
Additional notes on the changes I would have made to the thesis paper if given more time for revisions:
- State that our attempt at equalization is probably overcompensating, so probabilistic looks better than one would think at first from the data.
- Explain why the average sizes of the Probabilistic Plushy genomes are much bigger than the average sizes of the Non-Probabilistic Plushy genomes because many of the genes in the Probabilistic Plushies have a probability of 0, so the effective size will be smaller.
- Suggest future work on developing a more-fairer comparison to actually account for all computational resources and on initializing the sizes of probabilistic genomes differently.
- Add in section 4.1 that the evidence suggests that crossover appears particularly effective in the context of large, untuned genetic sources and discuss how it could have promising contributions to the GP field.
- Provide more tables that present the number of near-1s and near-0s of the Probabilistic Plushy genomes that Propeller outputs from the probabilistic runs.