Papers › Evolutionary Algorithms for Designing Reversible Cellular Automata

Evolutionary Algorithms for Designing Reversible Cellular Automata

25 May 2021arXiv:2105.12039archive 2025-07-28

Luca Mariot, Stjepan Picek, Domagoj Jakobovic, Alberto Leporati

Reversible Cellular Automata (RCA) are a particular kind of shift-invariant transformations characterized by a dynamics composed only of disjoint cycles. They have many applications in the simulation of physical systems, cryptography and reversible computing. In this work, we formulate the search of a specific class of RCA -- namely, those whose local update rules are defined by conserved landscapes -- as an optimization problem to be tackled with Genetic Algorithms (GA) and Genetic Programming (GP). In particular, our experimental investigation revolves around three different research questions, which we address through a single-objective, a multi-objective, and a lexicographic approach. The results obtained from our experiments corroborate the previous findings and shed new light on 1) the difficulty of the associated optimization problem for GA and GP, 2) the relevance of conserved landscape CA in the domain of cryptography and reversible computing, and 3) the relationship between the reversibility property and the Hamming weight.

PaperPDFCode

Code

rymoah/EvoRevCA officialmentioned in paper report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Tasks

Evolutionary Algorithms

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Methods

Class AttentionGA

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections