Reference library
Evolving Cellular Automata to Perform Computations: Mechanisms and Impediments
Paper summary
Evolves cellular automata for density classification and analyzes successive computational strategies. The study identifies innovation episodes and search impediments, including symmetry breaking that gives short-term gains while blocking stronger solutions.
Relevance to the project
A methodological reference for explaining behavior through rule and trajectory analysis. Evolution can discover mechanisms while the task and substrate remain predefined.
Improvement on one fixed task is not open-ended evolution.
Source record
- Reference ID
- article-https-csc-ucdavis-edu-evca-papers-mechimped-html
- Archived version
- Complete author-hosted working paper, two original PDF parts (17 + 27 pages); published counterpart Physica D 1994
- Summary provenance
- reference-library/papers/article-https-csc-ucdavis-edu-evca-papers-mechimped-html/metadata.json · summary
- Review status
- initial orientation summary; not a critical full-paper review
- Reading scope
- Selected abstract/opening and available closing discussion/conclusion passages in the preserved text extract; broader project notes provide context. No reproduction of experiments, exhaustive methods review, or equation/figure audit.